𝙄 𝙗𝙪𝙞𝙡𝙙 𝘿𝙖𝙩𝙖 𝙀𝙣𝙜𝙞𝙣𝙚𝙚𝙧𝙞𝙣𝙜 𝙨𝙮𝙨𝙩𝙚𝙢𝙨 𝙛𝙧𝙤𝙢 𝙩𝙝𝙚 𝙜𝙧𝙤𝙪𝙣𝙙 𝙪𝙥, 𝙀𝙏𝙇 𝙥𝙞𝙥𝙚𝙡𝙞𝙣𝙚𝙨, 𝘿𝙖𝙩𝙖 𝙒𝙖𝙧𝙚𝙝𝙤𝙪𝙨𝙚𝙨, 𝙞𝙣𝙩𝙚𝙜𝙧𝙖𝙩𝙞𝙤𝙣𝙨, 𝙖𝙣𝙙 𝘽𝙪𝙨𝙞𝙣𝙚𝙨𝙨 𝙄𝙣𝙩𝙚𝙡𝙡𝙞𝙜𝙚𝙣𝙘𝙚 𝙙𝙖𝙨𝙝𝙗𝙤𝙖𝙧𝙙𝙨. 𝙈𝙮 𝙜𝙤𝙖𝙡 𝙞𝙨 𝙨𝙞𝙢𝙥𝙡𝙚: 𝙜𝙞𝙫𝙚 𝙮𝙤𝙪𝙧 𝙩𝙚𝙖𝙢 𝙧𝙚𝙡𝙞𝙖𝙗𝙡𝙚 𝙙𝙖𝙩𝙖, 𝙖𝙪𝙩𝙤𝙢𝙖𝙩𝙚𝙙 𝙧𝙚𝙥𝙤𝙧𝙩𝙞𝙣𝙜, 𝙖𝙣𝙙 𝙙𝙖𝙨𝙝𝙗𝙤𝙖𝙧𝙙𝙨 𝙩𝙝𝙖𝙩 𝙢𝙖𝙠𝙚 𝙞𝙩 𝙚𝙖𝙨𝙞𝙚𝙧 𝙩𝙤 𝙨𝙚𝙚 𝙬𝙝𝙖𝙩 𝙞𝙨 𝙝𝙖𝙥𝙥𝙚𝙣𝙞𝙣𝙜 𝙖𝙣𝙙 𝙢𝙖𝙠𝙚 𝙗𝙚𝙩𝙩𝙚𝙧 𝙙𝙚𝙘𝙞𝙨𝙞𝙤𝙣𝙨. 𝙃𝙚𝙧𝙚’𝙨 𝙬𝙝𝙖𝙩 𝙄 𝙘𝙖𝙣 𝙝𝙚𝙡𝙥 𝙬𝙞𝙩𝙝: 𝟭. 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 & 𝗗𝗮𝘁𝗮 𝗪𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗶𝗻𝗴 🔹 Data Warehousing from scratch 🔹 SQL, Python & Data Modeling 🔹 Snowflake, BigQuery, Databricks & PostgreSQL 🔹 Database Design & cloud migrations 𝟮. 𝗘𝗧𝗟 & 𝗗𝗮𝘁𝗮 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 🔹 ETL / ELT pipeline development 🔹 APIs, CRMs, ecommerce & advertising data 🔹 Fivetran, Airbyte & dbt 🔹 Fixing broken or unreliable ETL pipelines 𝟯. 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 & 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱𝘀 🔹 Power BI & Tableau dashboards 🔹 Business Intelligence reporting 🔹 Data Visualization & KPI dashboards 🔹 Marketing, sales, finance & operations reporting 𝙏𝙤𝙤𝙡𝙨: Power BI | Tableau | SQL | Python | Snowflake | BigQuery | dbt | PostgreSQL | Fivetran | Airbyte | Looker | AWS | Azure | GCP 𝙒𝙚 𝙖𝙧𝙚 𝙖 𝙥𝙚𝙧𝙛𝙚𝙘𝙩 𝙢𝙖𝙩𝙘𝙝 𝙞𝙛 𝙮𝙤𝙪 𝙣𝙚𝙚𝙙: 𝟭. Data Engineer 𝟮. Data Engineering 𝟯. ETL Developer 𝟰. Data Warehouse Developer 𝟱. Business Intelligence Developer 𝟲. Power BI Developer 𝟳. Analytics Engineer 𝟴. Data Integration Specialist 𝟵. SQL Developer 𝟭𝟬. Tableau Developer 𝙄𝙛 𝙮𝙤𝙪 𝙣𝙚𝙚𝙙 𝙖 𝙨𝙚𝙧𝙞𝙪𝙨 𝙙𝙚𝙫𝙚𝙡𝙤𝙥𝙚𝙧 𝙩𝙤 𝙗𝙪𝙞𝙡𝙙 𝙮𝙤𝙪𝙧 𝙙𝙖𝙩𝙖 𝙨𝙮𝙨𝙩𝙚𝙢 𝙛𝙧𝙤𝙢 𝙨𝙘𝙧𝙖𝙩𝙘𝙝 𝙤𝙧 𝙛𝙞𝙭 𝙬𝙝𝙖𝙩 𝙮𝙤𝙪 𝙖𝙡𝙧𝙚𝙖𝙙𝙮 𝙝𝙖𝙫𝙚, 𝙨𝙚𝙣𝙙 𝙢𝙚 𝙖 𝙢𝙚𝙨𝙨𝙖𝙜𝙚.

Your dashboards are slow, your data sources don't agree with each other, and leadership has stopped trusting the numbers, I rebuild the analytics layer underneath, using dbt on Snowflake or BigQuery, so your team makes decisions on data you can actually defend. With over 11,000 hours logged and 80+ projects delivered on Upwork, I've worked with growth-stage SaaS startups, fintechs, retail and eCommerce operators, real estate firms, and global research organizations to design dbt-based data models, build end-to-end ETL/ELT pipelines, and deliver BI systems that eliminate reporting delays. A few projects I've led recently: CGIAR - Built a centralized enterprise analytics platform on Microsoft Fabric and Power BI, replacing fragmented reporting across a global research consortium. Sojo Industries - Designed a continuous intelligence layer delivering real-time visibility and enterprise-grade analytics for retail operations. Markets4U - Migrated a fast-growing fintech off Metabase, Oracle BI, and Vertica onto a high-performance analytics stack built for real-time decisions. Westwise - Centralized fragmented data sources to power marketing and sales insights for a legal services platform. ECAP - Delivered analytics and financial modeling for a private real estate investment firm managing strategic property portfolios. Voice AI Automation Company - Integrated Stripe, HubSpot, GA4, Google Ads, Linear, Pylon, and MongoDB into a unified, business-ready data model for an AI-first SaaS company. How I work across the analytics engineering stack: Data Modeling and Transformation - I build dbt models on Snowflake and BigQuery that turn raw, multi-source data into clean, analytics-ready datasets. Strong focus on testing, documentation, and modular design so your data layer stays reliable as it scales. Data Engineering and Pipelines - I design and maintain ETL/ELT pipelines using SQL, Python, and Apache Airflow across AWS, GCP, and Azure. Whether you need to ingest from APIs, sync SaaS tools, or move data between warehouses, I build pipelines that don't break when your business grows. Business Intelligence and Dashboards - I build interactive dashboards in Power BI, Tableau, and Looker Studio that turn analytics-ready data into clear, actionable insights for stakeholders. KPI tracking, executive reporting, self-service analytics — designed for the people who actually use them. Cloud and Warehouse Expertise - Deep work across Snowflake, BigQuery, PostgreSQL, and Redshift, with hands-on experience integrating GA4, HubSpot, Salesforce, Stripe, and other SaaS data sources into unified warehouses for cross-functional reporting. Why clients keep working with me: - 11,00+ hours logged, 100% Job Success Score, Top Rated Plus - End-to-end ownership from data ingestion through dbt modeling to dashboard delivery - I translate technical complexity into business outcomes, not jargon - Long-term clients rehire me for scale-up support, audits, and platform migrations - Available for project-based work and ongoing analytics engineering partnerships If your reports are slow, your data sources don't talk to each other, or you can't trust the numbers in your dashboards — let's talk. I'll audit your current stack, identify what's broken, and rebuild the foundation your team needs to make confident, data-driven decisions. Send me a message and I'll map out a plan tailored to your analytics, data engineering, or dashboard work — clear scope, real outcomes, no fluff.

With 8+ years of experience building end-to-end analytics solutions, I help businesses transform scattered data into modern, reliable analytics platforms that support confident, data-driven decisions. I design and build scalable analytics foundations using Microsoft Fabric, Azure Data Services, GCP, BigQuery, dbt, SQL, Python, and ETL/ELT pipelines to consolidate data from CRMs, ERPs, marketing platforms, e-commerce systems, and other business applications. On top of these trusted data models, I develop intuitive dashboards and reports in Power BI and Looker, giving stakeholders access to consistent KPIs and actionable insights. I also integrate AI-powered analytics, including natural language querying and AI-assisted insights, where they add value to the reporting experience. Many organizations struggle with inconsistent KPIs, manual reporting, fragmented data across CRMs, SaaS tools, spreadsheets, and cloud platforms, or dashboards that look good but do not scale. I solve these problems by building structured analytics systems that improve data quality, reduce manual work, and make reporting easier to trust and use. 📊My Services / Deliverables: • Business Intelligence Real-time insights into revenue, operations, and KPIs that leadership teams can rely on. • Data Pipelines and ETL Engineering Robust ETL/ELT pipelines that power dashboards, analytics, and AI workflows which scale as your data grows. • Data Infrastructure and Modeling Bring together data from CRMs, SaaS, Marketing, Ecommerce and other platforms into a unified data foundation while resolving modeling challenges such as data validation, enrichment, error handling, multi-source attribution, identity resolution and inconsistent metrics. • AI-Powered Analytics Leverage Generative AI and NLP to generate actionable insights, summarize data, detect anomalies, and interact with dashboards using natural language queries. • Workflow Automation Connect CRMs, ERPs, and SaaS tools with Power Automate, Zapier, n8n, or custom Python workflows to automate processes. 🛠️Core Skills & Tools: • BI & Visualization: Power BI, Looker, Google Data Studio, Metabase • Data Engineering & Modeling: SQL, Python, dbt, Power Query, Azure Data Factory, Airflow • Data Platforms: Fabric, Azure Synapse, Snowflake, BigQuery, Redshift • Automation: Power Automate, Zapier, n8n, API integrations, Agents • AI Integration: ML/AI pipelines, OpenAI API, Azure OpenAI I work with teams that want practical analytics outcomes, not just visual dashboards. If you need an analytics specialist who can also handle the data engineering and automation behind the reporting, I can help.

I'm Kunal Sharma — an Analytics Engineer and Data Leader with 13+ years building production-grade analytics for global enterprises (Sanofi, Otsuka, Amgen) and fast-growing startups. Trusted by 30+ clients across 8+ industries. Top Rated Plus, 100% Job Success. I do two things well. I build the governed, well-modeled data foundations that modern analytics depends on — and I use data to answer real business questions and drive decisions. Plenty of people can do one or the other; the combination is where I add the most value. I can architect the warehouse and then sit with a stakeholder's messy question — why is revenue moving, which segments actually retain, what's driving the drop — and turn it into a clear, defensible answer. On the engineering side: dbt transformations, dimensional and semantic models, standardized KPIs, and clean BI layers, increasingly built so that AI agents can query them safely too — through self-service BI and natural-language / agentic interfaces (MCP servers, LLM tooling), so teams and their tools get trusted answers without writing SQL. As a data lead I've owned data platforms end to end — defining strategy, designing scalable architectures on modern warehouses and lakehouses, standardizing metrics governance across teams, and driving self-service adoption so insights stay consistent, trusted, and decision-ready. I'm known for solving complex data problems with clarity and business context. I also lead a carefully selected analytics team under my direct supervision, letting me deliver high-quality work efficiently and at competitive rates. Hands-on or through my team, I guarantee production-quality data models, clean BI layers, and actionable insights. —————————— Services Offered 1. Analytics Engineering & Data Modeling - dbt-based transformations & production-grade analytics models - Dimensional & semantic modeling for warehouses and lakehouses - Data quality testing, CI/CD & documentation - Incremental / Iceberg patterns for scale - API-driven extraction & reverse ETL via custom Python "Unparalleled attention to detail" — CEO, Scaleleap 2. Data Analysis & Business Problem-Solving - Turning ambiguous business questions into clear, decision-ready answers - Revenue, retention, cohort & segmentation analysis - Financial metrics reconciliation & root-cause investigation - Customer / user behavior and spend-distribution analysis - Insight synthesis and recommendations leadership can act on "Focused on the big picture" — Director, Axtria Inc "Strong as a data scientist" — Principal, Axtria Inc 3. AI-Ready Data & Agentic Analytics - MCP servers for natural-language & agentic querying of governed data (AWS Bedrock AgentCore, FastMCP) - Semantic layers & governed views that make warehouses safe for LLMs and agents - LLM use-cases, prompt engineering & agentic dev workflows (Claude Code) - Predictive modeling & machine learning 4. Business Intelligence & Self-Service Analytics - Executive & operational dashboards (Power BI, Tableau, QuickSight, Looker) - Standardized KPI frameworks & metrics definitions - Self-service BI enablement for business teams - Ongoing reporting, governance & performance optimization "Top presentation skills" — Manager, Sanofi "Skilled data visualization guru" — Co-Founder, TripleLine Brands 5. Data Leadership, Strategy & Governance - Data strategy, analytics roadmaps & architecture design - KPI standardization & metrics governance across teams - Analytics operating models for scale & consistency - Stakeholder alignment & decision-focused insights - End-to-end analytics project leadership "Communicates very well" — Founder, SellerPlex —————————— Tools & Technologies BI & Visualization Power BI, Tableau, Amazon QuickSight, Looker, Metabase, Google Sheets, Excel Analytics Engineering & Warehousing dbt, SQL, AWS S3, Amazon Athena, Apache Iceberg, Redshift, Snowflake, BigQuery, Azure SQL, Azure Synapse Pipelines, Automation & CI/CD GitHub, CI/CD, dbt Cloud / Core, reverse ETL, Power Query, Power Automate, AWS orchestration AI, Agents & Advanced Analytics Python, Pandas, Polars, Scikit-learn, MCP (Model Context Protocol), AWS Bedrock / AgentCore, Claude Code, LLM / GenAI tooling —————————— Thanks for reading. If you'd like to work together, send me a message using the button in the top right. Looking forward to connecting!

🏆 Top Rated Plus 🌟 100% Job Success 🤝 Satisfied Clients ⏱ Quick Turnaround 📞 Clear Communication Why work with me? Proven Experience: 💎 Backed by 15+ years of delivering results through scalable, cost-efficient data solutions. Technical Expertise: 💎 AI-Data Architecture: I deliver real-world-ready data through automated, reliable pipelines. The new AI era requires a new data platform. 💎 Conversational Analytics & AI Agents: Enable users to chat with their data through AI-driven interfaces. Google Conversational Analytics API and Gemini Enterprise 💎 Data Visualization: Skilled in Looker, Looker Studio, Power BI, Tableau, Superset, and others. 💎 Data Web Portals: Skilled in developing custom embeddable solutions and full web platforms under your own brand and domain. 💎 Database Management: Expertise in SQL (BigQuery, SQL Server, Oracle, MySQL, PostgreSQL, Snowflake) and NoSQL systems. 💎 ETL: Experience with both streaming and batch pipelines using Airflow, Apache Beam, Kafka, Debezium, Pub/Sub, and others. 💎 Data Modeling: Proficient with dbt, Dataform, and PySpark. 💎 Version Control: Comfortable with Git-based tools (GitHub, Bitbucket, GitLab, Azure DevOps). 💎 Cloud Platforms: Certified and experienced in GCP, AWS, and Azure. 💎 Unstructured Data: JSON, XML, Excel, Google Sheets. 💎 GA4 Data: Google Analytics 4 for advanced analysis. Soft Skills & Work Ethic: 💎 Versatile & Adaptive: Quick to learn new tools, roles, and business domains. 💎 Value-Driven: Focused on delivering high-impact outcomes with cost-efficiency. 💎 Detail-Oriented: Committed to precision and quality in every task. 💎 Reliable & Time-Conscious: Consistent delivery of high-quality work on time. 💎 Leadership: Capable of guiding teams and leading initiatives when needed. 💎 Analytical: Skilled at breaking down complex problems and finding effective solutions. 💎 Collaborative: Strong team player, effective in multidisciplinary environments. Scalable Technical Capacity: I’m supported by a network of 15+ specialists, including Solution and Data Architects, Developers, Designers, Process Specialists, DevOps Engineers, Machine Learning Engineers, Data Scientists, Data Analysts, and more. We work collaboratively to ensure your project receives the strongest possible technical support, from strategy to execution. How I approach projects: - Kick-off meeting to review requirements and deliverables - Action plan development using a project management tool - Weekly demo meetings to showcase progress - Detailed time and task tracking - Continuous feedback loop to ensure alignment and improvement - Complete documentation of the solution

Most companies already have data. What they often lack is a reliable system that turns that data into something consistent, accurate, and usable across the business. I help companies move from fragmented data and manual reporting to structured analytics systems by building pipelines, defining metrics, and creating scalable data models that teams can actually trust. Whether you're trying to understand revenue performance, customer behavior, marketing ROI, or operational efficiency, I focus on making sure your data is not just available, but clean, well-modeled, and decision-ready. With 3+ years of experience in data analytics and business intelligence, I now work at the intersection of analytics and data engineering: building modern data workflows using tools like dbt, SQL, and cloud data warehouses. Recent Impact • Built structured data models and transformation layers that standardized reporting across teams and improved consistency in key business metrics • Designed analytics workflows that reduced manual reporting effort and improved data accessibility for stakeholders • Developed cohort and behavioral models that clarified retention patterns and supported more targeted growth strategies • Identified and resolved data inconsistencies across multiple sources, improving trust in reporting and reducing discrepancies How I Help Businesses ✔ Build and optimize ELT pipelines for clean, reliable data flow ✔ Design data models (fact/dimension tables, star schemas) for scalable analytics ✔ Implement dbt transformation layers for structured, maintainable data workflows ✔ Define and standardize business metrics across teams ✔ Validate and reconcile data to ensure accuracy and consistency ✔ Write optimized SQL for large datasets and complex transformations ✔ Build dashboards on top of well-structured data models ✔ Translate business questions into structured data solutions Types of Projects I Work On • End-to-end analytics engineering (raw → staging → marts → dashboards) • dbt project setup, modeling, testing, and documentation • Data pipeline orchestration (Airflow, GitHub Actions, or similar tools) • Data modeling for analytics (fact tables, dimensions, metric layers) • Marketing and product analytics infrastructure • Revenue and performance analytics systems • Data validation, testing, and reconciliation workflows Tools & Technologies Data Warehousing & Modeling BigQuery dbt (modeling, testing, documentation) SQL (advanced: joins, CTEs, window functions) Orchestration & Workflow Apache Airflow (learning / applied) GitHub Actions (pipeline automation) Analytics & BI Power BI Looker Studio Data Processing & Analysis Python (pandas, matplotlib, seaborn) Excel / Google Sheets Data Sources GA4 (event-level data) CRM systems Marketing platforms SQL databases Google Cloud Platform Portfolio Projects Modern Data Stack Project (dbt + BigQuery) Built a structured analytics pipeline using dbt to transform raw data into staging and mart layers, enabling scalable reporting and consistent metric definitions Marketing Data Pipeline & Performance Analysis Integrated GA4 and campaign data into a unified dataset for evaluating conversion, attribution, and ROI Customer Cohort & Retention Modeling Developed cohort-based models to track lifecycle behavior and identify high-value segments Operational KPI Tracking System Designed a centralized reporting system to monitor performance and support leadership decision-making Why Clients Work With Me • I build systems, not just reports • Strong focus on data accuracy, validation, and testing • Ability to structure messy, real-world data into usable models • Experience working with modern data stack tools (dbt, warehouses, pipelines) • Clear communication across technical and business teams • Solutions designed to scale as your data grows My Approach 1️⃣ Understand the business problem and data landscape 2️⃣ Structure and clean raw data sources 3️⃣ Build transformation layers (dbt / SQL models) 4️⃣ Define metrics and validate data accuracy 5️⃣ Deliver reporting systems and insights that support decisions If you're looking for someone who can not only analyze your data but also build the systems that make your data reliable, scalable, and easy to use, feel free to reach out. Tell me about your data stack and what you're trying to achieve

I'm a Senior Data Engineer with 8+ years of strong technical expertise in building reliable and scalable data infrastructure, from data ingestion to transformation to warehousing, streaming, and data analytics, specializing in dbt, Snowflake, Airflow, Databricks (and more) across AWS, Azure, and GCP, with robust ELT and ETL pipelines. If your data pipelines are brittle, your data warehouse is slow, or your data was never built to scale, that is exactly what I fix, with fault tolerance, observability, and audit-ready quality engineered in from day one. I cover the full data engineering lifecycle: batch and real-time data pipelines, Modern Data Stack builds, lakehouse architecture, cloud and warehouse data migration, governance, and the data foundations that feed modern systems. 🎯 Core Expertise: ✅ Data Pipelines & Orchestration: End-to-end batch and real-time pipelines with Apache Airflow, Dagster, Prefect, AWS Step Functions, and Azure Data Factory. Idempotent, schema-drift tolerant, and monitored so failures surface before they reach your stakeholders. ✅ Cloud Warehousing & Lakehouse: Snowflake, BigQuery, Amazon Redshift, Databricks, and Microsoft Fabric, with Delta Lake and Apache Iceberg lakehouse foundations governed through the Glue Data Catalog and Lake Formation, with Athena and Redshift Spectrum for serverless queries, Medallion Architecture, partitioning, and performance tuning. ✅ Data Transformation & Modeling: dbt (Core and Cloud), SQLMesh, Spark and PySpark on EMR and AWS Glue, Star Schema and dimensional modeling, analytics engineering best practices, full test coverage, and CI/CD for data models. ✅ Streaming & Real-Time Analytics: Distributed streaming with Apache Kafka, Flink, Spark Structured Streaming, Kinesis, and Pub/Sub, including exactly-once semantics, dead-letter queues, CDC, and end-to-end latency guarantees. ✅ Data Ingestion & Integration: Fivetran, Airbyte, Matillion, Stitch, Hevo, Meltano, and custom CDC pipelines for near-real-time sync across structured, semi-structured, and unstructured sources. ✅ Data Quality, Governance & Observability: Automated data quality frameworks, SLA monitoring, auditable lineage, data catalog and metadata management, and observability that catches bad data early. ✅ Cloud Migration & Modernization: Zero-downtime migration handled end to end, from legacy warehouse assessment through cutover, with zero data loss and minimal downtime, replacing brittle ETL and ELT with a clean Modern Data Stack. ✅ AI-Ready Data Infrastructure: Pipelines engineered to feed LLMs and ML systems with clean, structured, high-quality data, from ingestion through transformation to serving. ------------------------------------------------------ ⚙️Tech Stack: ⚡ Warehouses & Lakehouse: Snowflake | BigQuery | Redshift | Databricks | Microsoft Fabric | Athena | Delta Lake | Iceberg ⚡ Transformation: dbt | SQLMesh | Spark | PySpark | AWS Glue | EMR | Star Schema | Medallion Architecture ⚡ Orchestration: Airflow (GCP Cloud Composer and AWS MWAA) | Dagster | Prefect | Azure Data Factory | Step Functions ⚡ Streaming: Kafka | Flink | Kinesis | Pub/Sub | Spark Structured Streaming | ClickHouse ⚡ Ingestion: Fivetran | Airbyte | Matillion | Stitch | Hevo | Meltano | CDC ⚡ Governance & Catalog: Glue Data Catalog | Lake Formation | Unity Catalog | Microsoft Purview | Dataplex ⚡ Cloud: AWS | GCP | Azure ⚡ Languages: Python | SQL (Snowflake, BigQuery, T-SQL, PL/pgSQL) | FastAPI ⚡ Databases: PostgreSQL | MySQL | SQL Server | DynamoDB | MongoDB ⚡ BI & Reporting: Looker | Tableau | Power BI | GA4 | Metabase | Superset | Streamlit | Grafana ------------------------------------------------------ ⭐ What Clients Say: 🏅 "Adarsh rebuilt our analytics pipeline on Snowflake, Airflow, and dbt, giving us reliable, version-ready data. Reporting accuracy improved overnight, and we can finally trust the numbers." – Anita, Head of Product, FinTech SaaS 🏅 "He designed a zero-downtime migration to a modern data warehouse that cut query latency by more than half while keeping our SLAs intact." – Daniel, VP of Data, AdTech Firm 🏅 "Clean architecture, solid dbt models, and Airflow pipelines running without issues for months. He brought a level of engineering discipline we hadn't seen from a data consultant before." – Mark, Director of Data Engineering, E-commerce Startup 🏅 "We came to him with a Spark pipeline costing us a fortune and delivering stale data. He restructured the workflow logic and cut processing time by 70%." – Leo, Head of Analytics, HealthTech SaaS ------------------------------------------------------ 🏆 TOP RATED PLUS | EXPERT-VETTED | Top 1% on Upwork | 8+ Years Experience | 100% Job Success 🚀 Ready to build a scalable, production-ready data infrastructure to turn your raw data into reliable, actionable business insights? Click the 'Invite to Job' button on the top right, and let's discuss your data pipeline!

I design and build reliable data platforms for product, marketing, and game analytics, from event collection and API integrations to warehouses, analytical models, BI dashboards, and AI assistants connected through MCP servers. I work across the full data lifecycle: data sources → ingestion → raw storage → warehouse → transformations → metrics → dashboards and agents My focus is practical architecture: systems that are understandable, maintainable, cost-conscious, and useful to the people making business decisions. What I can help you build - ETL and ELT pipelines using SQL and Python - Batch and event-driven data ingestion - BigQuery and ClickHouse analytics platforms - dbt, Dataform, and SQLMesh transformation projects - Dimensional, OBT, and OLAP data models - Product, marketing, and game analytics datasets - Attribution, ROAS, retention, churn, funnel, and cohort reporting - Event-tracking plans and event-schema design - Metabase dashboards and semantic reporting layers - API and advertising-platform integrations - Dockerized data services and cloud or VM deployments - Monitoring, recovery, and maintainable operational workflows - OpenCode and OpenClaw agent environments for data and analytics engineering - Reusable knowledge-backed skills and MCP integrations for databases, documentation, and operational tools - Agent task routing, memory, permissions, and validation workflows Data integration and connector experience I have experience as Data Integration Support Specialist, I work hands-on with connectors for Meta Ads, LinkedIn Ads, TikTok Ads, Microsoft Ads, X Ads, Reddit Ads, Shopify, HubSpot, and Google Search Console. This includes investigating authentication and API issues, understanding platform-specific metrics and dimensions, resolving data discrepancies, and helping customers work with changing schemas and connector limitations. Relevant project experience: I designed and built Rawbbit, a self-hosted open-source event analytics platform for game development teams. The system collects application events through an API, buffers them with NATS JetStream, stores immutable raw data as partitioned Parquet files, loads analytical data into ClickHouse using dbt, and provides reporting through Metabase and AI agents. Building Rawbbit expanded my practical experience with event-driven architecture, object storage, ClickHouse modeling, Docker Compose deployments, observability, backup and recovery design, and data-platform ownership. AI-assisted engineering workflows I also design OpenCode and OpenClaw environments for data and analytics engineering. This includes configuring specialized agents, building reusable knowledge-backed skills, defining task-routing and permission boundaries, and integrating external systems through MCP. My focus is not generic prompting. I build agent environments grounded in project documentation and tested workflows, so they can assist reliably with SQL, data modeling, infrastructure, documentation, and operational tasks. Technology - SQL, Python, dbt, Dataform, SQLMesh - BigQuery, ClickHouse, PostgreSQL - Parquet, GCS, S3-compatible object storage - GCP: Cloud Run, Pub/Sub, Scheduler, Secret Manager - NATS JetStream, Docker, Linux VMs - Metabase and Tableau - Meta Ads, Google Ads, AppsFlyer, AppLovin, Appodeal, Singular, App Store Connect, and other APIs If you need an individual pipeline, a warehouse and transformation layer, or an end-to-end analytics platform, I can help turn the requirements into a system your team can operate and trust.

A marketing data scientist specializing in the Google Stack, fluent in SQL, Python & Javascript. - Cloud: Google Cloud Platform (GCP). - Data Visualization: Looker Studio & Power BI. - Data Engineering: Cloud Composer (Apache Airflow) & Cloud Functions. - Data Modeling: BigQuery, dbt (Data Build Tool) & Snowflake. - CI/CD: Github Actions. - Analytics: Google Analytics 4 (GA4) & Mixpanel. - Tracking: Google Tag Manager (GTM), server side, cross domain & user tracking. - ETL: Airbyte. - Machine learning: Marketing Mix Modeling (MMM), Multi-Touch Attribution (MTA), Uplift Modeling (Incrementality). Let's connect and transform your data into actionable insights!

Senior AI/LLM engineer for enterprise teams. Built a system that saved 40 hrs/week of expert time by automating knowledge retrieval across 23 years of project data. I build for production, not demos. How I Can Help You Scale: ✅ AI Agent Development & Generative AI: I ship production-grade multi-agent systems, RAG pipelines, and agentic workflows using LangGraph, LlamaIndex, Claude, and GPT-4. I design the full intelligence layer: memory architecture, retrieval logic, orchestration, and evaluation frameworks and guardrails. ✅ Data Engineering & ETL/ELT: I architect clean, scalable data warehouses in Snowflake, Microsoft Fabric, and Redshift. My pipelines built with Apache Airflow, dbt, and Airbyte are designed to be reliable, well-documented, and maintenance-free. I have delivered full Microsoft Fabric medallion architectures from Bronze through to Gold and the Semantic Model layer for enterprise clients operating across multiple countries. ✅ Machine Learning & Predictive Analytics: From 15-year demand projections for industrial firms to stock return pipelines analysed over 23 years of market data, I turn raw numbers into high-conviction forecasts. My models combine econometric rigour with modern ML to handle real-world uncertainty, not just clean benchmark datasets. ✅ Business Intelligence & Dashboards: I create BI-ready semantic models and intuitive dashboards in Power BI, Looker Studio, and Apache Superset, connected to production-grade data models underneath, not spreadsheets dressed up as dashboards. Why Clients Work With Me: ✅ I have worked across carbon markets, fintech, non-profits, supply chain, SaaS, and logistics. I understand the domain before I touch the stack, not just the tools. ✅ I operate as an individual engineer, technical lead, or AI product manager depending on what the engagement needs. ✅ My work is clean and well-documented. I communicate in plain English, so I embed into teams without friction and hand over systems that do not fall apart after I leave. I am available for project-based builds or ongoing retainer engagements. Drop me a message with a rough description of the problem you're solving, and let's collaborate!