Top Rated Plus | 100% Job Success | Founder, DataNicely I help growing organizations fix reporting that can't keep pace with the business — when metrics don't align, dashboards aren't trusted, and leadership needs clearer, more reliable answers. I design analytics and reporting systems executives can depend on and teams actually use, enabling decisions to be driven by consistent, trusted data instead of spreadsheets and guesswork. As founder of DataNicely, I partner with leadership teams to bridge the gap between analytics strategy and execution — from defining KPIs and reporting roadmaps to building automated dashboards and data pipelines that eliminate manual effort. I also build AI agents on top of that clean data layer, so teams can ask questions of their data in plain language, specific to their role, without needing a data analyst in the room. With over 13 years of experience in analytics and data engineering, I've led initiatives across financial services, restaurant groups, nonprofits, and e-commerce — helping organizations centralize data, align metrics, and make confident, data-driven decisions. ⸻ Core Services • Analytics infrastructure design and data strategy consulting • Tracking cleanup and implementation (GA4, GTM, Meta Pixel, Conversions API) • AI-powered analytics agents (built on leading LLMs) • KPI definition, metric alignment, and reporting frameworks • Dashboard development (Power BI, Tableau, Sigma Compute, Looker Studio) • ETL/ELT pipelines, data integration, and workflow automation (BigQuery, dbt, Make, Python) • Automated reporting, monitoring, and real-time alerting ⸻ Tech Stack BigQuery | dbt | GA4 | GTM | Meta Pixel | Make | Power BI | Tableau | Snowflake | Looker Studio | Python ⸻ If your data infrastructure isn't keeping up with your business, that's the problem I solve — from the ground up.

I am an experienced Data Engineer with 5 years of hands-on experience in ETL, Data Engineering, Data Modeling, Data Integration, and Data Warehousing. My work mainly emphasizes reliability, efficiency, challenge, and simplicity. If you are looking for someone with a broad skill set who can work as a team member and take on the responsibilities of the tasks. I have experience and knowledge in the following areas, tools, and technologies: ►Data Storage: S3, Azure Storage, Google Cloud Storage ► Data Warehouse: Google BigQuery, Snowflake, Azure Synapse Analytics ► DATABASES: SQL Server, MySQL, PostgreSQL, MongoDB, Oracle, Google Cloud Big Table ►Data Lake: Azure Data Lake Storage, AWS Lake Formation ► Data Transformation, Data Integration, Data Governance, Data Quality: Azure Data Factory, Azure Synapse, Amazon Glue, Fivetran, DBT ► Monitoring Tools: Amazon Cloudwatch, New Relic, Dynatrace, Datadog ► BI, Visualization, Data Analyst: Power BI, Metabase, Sigma BI ► OTHER SKILLS & TOOLS: SQL, Python, Rest API ► I can also work on different technologies and tools if required

Senior Data Engineer with more than 5 years of professional experience in Cloud Data/Software Engineering in major Nordics companies. - built end to end Data Analytics platforms on cloud for multiple companies in US and Europe (as a DE Consultant in major Data Service Provider) - developed data intensive streaming applications for various data realms (as a DE Consultant in major Data Service Provider) - set up Infrastructure on Cloud for the whole Data Analytics Platform including CI/CD (as a DE in Igaming company ) - developed Data Intensive applications and engines for customer retention , communication and loyalty programs (as a DE in Igaming company ) Main Areas of Expertise: - Analytical Platform on Cloud - Analytical Platform on Cloud with Data Lakehouse - Data Integration (streaming and batch) - Data applications for any usecase - Data Ops

With 6+ years of experience as a Data Engineer & AI Specialist, I design ETL/ELT pipelines, AI-driven analytics, and scalable cloud solutions that transform raw data into intelligence. I work across AWS, GCP, Azure, and Snowflake to deliver data engineering, AI automation, and real-time analytics for industries like fintech, real estate, and SaaS. From AI-powered RAG pipelines to enterprise-scale data warehouses, I create solutions that are robust, cost-efficient, and production-ready. 🧠 Generative AI & Machine Learning LLMs: OpenAI (GPT-4o), Gemini, Claude, LLaMA, Hugging Face, LangChain, LlamaIndex RAG Pipelines & Vector Databases: Pinecone, FAISS, Weaviate AI Tools: Prompt Engineering, Fine-Tuning, Model Deployment, MLflow, TensorFlow, PyTorch NLP & Forecasting: Topic modeling, Churn prediction, Real-time analytics ⚙️ Data Engineering & Pipelines Orchestration & ELT: Airflow, DBT, Dagster, Prefect, Fivetran, Airbyte, Meltano, dlt ETL / Data Pipelines: Python, SQL, Spark, Dask, Pandas, NumPy Data Warehousing: Snowflake, BigQuery, Redshift, Databricks, Delta Lake, DuckDB APIs & Automation: FastAPI, Flask, REST APIs, Web Scraping, API Integrations Scraping & Data Extraction: Scrapy, Selenium, Playwright, BeautifulSoup, Cloudflare Bypass, Proxy Rotation 📊 Data Visualization & Analytics Tableau, Looker, Power BI, Google Data Studio, QuickSight, Plotly, Dash, Seaborn, Matplotlib Real-time dashboards & business intelligence for decision-making ☁️ Cloud & DevOps AWS: Lambda, Glue, Athena, S3, Redshift GCP: BigQuery, Dataflow, Cloud Run, Vertex AI Azure: Data Factory, AI Services, Synapse Docker, CI/CD, Serverless, Cloud-native AI 🛠 Workflow Automation n8n, Make (Integromat), Zapier, Airtable, No-Code Data Engineering 🎯 Keywords (for Upwork SEO) Python, SQL, Python, Apache Spark, PySpark, Snowflake, Spark, BigQuery, Redshift, Databricks, Databricks Platform, Spark, ETL, ELT, DBT, Airflow, Prefect, Dagster, Fivetran, Airbyte, Meltano, MLflow, Hugging Face, TensorFlow, PyTorch, LLM, RAG, LangChain, Vector Databases, Pinecone, Weaviate, FAISS, NLP, Forecasting, Scrapy, Selenium, BeautifulSoup, Playwright, API Development, Web Scraping, Data Warehousing, Data Engineering, Automation, n8n, Make, No-Code Pipelines, Cloud Data Engineering, Database, API Integration, Data Analysis, Data Science, Database Architecture, AI Agent Development, AI App Development 🔖 Hashtags #DataEngineering #ETL #ELT #AIEngineering #LLM #GenerativeAI #Snowflake #BigQuery #Databricks #ApacheAirflow #DBT #RAG #LangChain #VectorDB #PythonDeveloper #APIAutomation #WorkflowAutomation #n8n #Make #NoCodeDataEngineering #MachineLearning #CloudData #Database #APIIntegration #DataAnalysis, #DataScience #ApacheSpark #Spark #AIDataEngineering #WorkflowAutomation #Snowflake #BigQuery #ApacheAirflow #PythonDeveloper #NoCodeDataEngineering #n8n #Make #dbt #PySp #DatabaseArchitecture #DatabricksPlatform #AIAgentDevelopment #AIAppDevelopment

I help businesses build scalable analytics systems, automate reporting workflows, and turn raw data into actionable business insights using modern data stack technologies and AI-powered analytics. Over the last 4+ years, I’ve worked with startups, agencies, and enterprise clients across Upwork and Fiverr, delivering high-impact analytics solutions in marketing, sales, operations, and business intelligence. My expertise combines analytics engineering, BI development, and AI integrations to help companies move beyond static dashboards into intelligent data systems. What I can help you with: • Analytics Engineering (dbt, Snowflake, SQL) • Power BI & Tableau Dashboards • AI-Powered Reporting & Insight Generation • ETL / ELT Data Pipelines • Marketing Analytics & Attribution Reporting • Python Automation & Data Processing • Natural Language to SQL Systems • KPI Monitoring & Executive Reporting • AI Analytics Automation using LLM APIs • Data Modeling & Warehouse Optimization Tech Stack: Snowflake, dbt, Power BI, Tableau, SQL, Python, FastAPI, OpenAI API, LangChain, Streamlit, Excel, Alteryx I focus on building scalable, maintainable, and business-focused analytics systems that help teams make faster and smarter decisions. If you're looking for someone who understands both the technical and business side of analytics, let’s connect.

As a Top Rated Plus engineering partner with over 14 years of hands-on experience, I bridge the gap between robust product engineering, high-throughput data infrastructure, and cutting-edge GenAI implementations. I have built dozens of technically successful applications from scratch, scaled secure data pipelines, and transitioned legacy monoliths into high-performance, serverless microservices used by Fortune 500 companies. My philosophy centers on structural risk mitigation for enterprise projects: I prioritize SOLID design principles, Test-Driven Development (TDD), Agile/Scrum methodologies, clean architecture, cost efficiency, and rigorous documentation. Having successfully delivered projects across heavily regulated industries - including eCommerce, healthcare, and SaaS platforms - I ensure your systems run smoothly, scale infinitely, and optimize cloud spend. --------------------------------------------------------------------------------------------------------------------- WHAT I DO & HOW I CAN HELP YOUR TEAM: AI, LLMs, & Intelligent Agents: ~ Architecting advanced retrieval-augmented generation (RAG) pipelines, building context-aware AI Agents, and integrating Large Language Models (LLMs) safely into enterprise ecosystems. Full-Stack Product Architecture: ~ Designing and engineering scalable web and mobile solutions from scratch. Expert in the MERN/MEAN stack, serverless microservices, and modern state management. Data Engineering & Analytics Stack: ~ Building comprehensive modern data stacks, managing automated ETL/ELT pipelines, and deploying cost-effective cloud data warehouses. Business Intelligence (BI) & Advanced Analytics: ~ Turning complex raw data into actionable enterprise insights via custom dashboards, real-time analytics engineering, and advanced modeling. DevOps, Infrastructure & Team Leadership: ~ Managing CI/CD deployment pipelines, containerization, and Infrastructure as Code (IaC). Collaborative partner to PMs, designers, and clients; experienced in mentoring, interviewing, educating, and code reviews. --------------------------------------------------------------------------------------------------------------------- TECH STACK & KEYWORD MATRIX: 1. Generative AI & Data Engineering [ AI/LLM Execution ]: GenAI, LLMs, RAG, AI Agents, Prompt Engineering, Vector Databases [ Data Warehousing & Platforms ]: Snowflake, Databricks, BigQuery, AWS EMR, Data Lakes [ ETL/ELT Tools ]: dbt, Apache Spark, Pandas, Pentaho, Talend, Informatica, Snaplogic [ BI & Analytics ]: Power BI, Tableau, AWS QuickSight, Looker Studio 2. Full-Stack Frameworks & Languages [ Core Languages ]: Python, TypeScript, JavaScript (ES13+), Go, Bash [ Frontend Ecosystem ]: React, Next.js, Angular, Vue.js, React Native, Redux, Zustand, HTML5, CSS/SCSS, Webpack, Babel, Responsive Web Design, SEO [ Backend Ecosystem ]: Node.js, NestJS, Express.js, tRPC, Apollo Server 3. Infrastructure, DevOps & Databases [ Cloud Architecture ]: AWS (Lambda, SQS, ECS, S3, EC2, API Gateway, CDK), Azure, Google Cloud Platform (GCP) [ Infrastructure as Code & DevOps ]: Terraform, CloudFormation, Docker, CI/CD Pipelines, Serverless Framework, Nginx, Nx Monorepo, Lerna [ APIs & Messaging ]: GraphQL, REST, gRPC, WebSockets, Apache Kafka, RabbitMQ [ Databases & ORMs ]: PostgreSQL, MySQL, MongoDB, Firebase, Redis, Prisma 4. Team & Collaboration Tools [ Methodologies ]: Agile, Scrum, Design Principles, Design Patterns, SOLID, TDD, Clean Code [ Platforms ]: Git, GitHub, Jira, Slack, Zoom, Technical Planning, Estimating, Mentoring, Code Reviews, Interviewing --------------------------------------------------------------------------------------------------------------------- PROJECT LIFECYCLE ROLES AVAILABLE FOR: - Principal AI / Data Engineer - Senior Full-Stack Developer & Software Architect - Technical Consultant & Business Intelligence Specialist - Mobile Development Lead (Web & Mobile Solutions) --------------------------------------------------------------------------------------------------------------------- Daily Availability: 8-12 Hours/Day (Depending on project scope, role, and comfortability) If you have an active project requiring robust data architecture, seamless full-stack execution, and a reliable delivery partner, let's connect and discuss how to bring your solution to life.

Most companies don't have an AI problem or a data problem. They have a "we can't trust our numbers and half our work is manual" problem. I fix both. I build the data pipelines and warehouses that give you clean, reliable data — and the AI agents, RAG systems, and automation that put that data to work. Pipelines that don't break at 2am, and AI that ships to production instead of dying as a demo. I've done this for startups, agencies, and growing teams: moving and modeling messy data, automating operations and support, processing documents, and building internal tools that answer questions instead of creating more tickets. A few recent projects: - A LangGraph multi-agent system that researches, writes, and validates reports on its own — with evaluation and human review built in, so the output is actually usable. - ETL/ELT pipelines and analytics warehouses (dbt, Airflow, Snowflake/BigQuery) with quality checks and monitoring, so teams stop arguing about whose numbers are right. - Document pipelines that pull data out of PDFs, invoices, and contracts using OCR + LLM extraction, validate it, and land it in a database. - Real-time voice agents (Twilio, Deepgram, ElevenLabs, OpenAI Realtime) for booking, support, and lead qualification. - RAG knowledge assistants connected to docs, databases, and CRMs that give accurate answers with sources — not hallucinations. - Power BI dashboards and reporting layers that give teams one source of truth they can actually self-serve. How I work: I care about the business outcome, not the buzzword. Everything I ship is built to run reliably with monitoring in place. I communicate clearly, respond fast, and own the work end-to-end from architecture to deployment. Tools I reach for: Python, SQL, dbt, Airflow, Spark, Snowflake, BigQuery, Databricks, Postgres for data — and LangGraph, LangChain, OpenAI, Claude, FastAPI, Pinecone/Qdrant, Twilio, and Power BI for the AI and delivery side. If you need a solid data foundation, AI built on top of it, or both — let's talk.

I build marketing analytics and attribution systems that show exactly which campaigns, channels, and product behaviors drive revenue, so growth teams can scale what works and cut what doesn’t. With 5+ years as a Data Engineer and Analytics Consultant, I partner with marketing, product, RevOps, and executive teams to stitch together ad platforms, analytics tools, CRMs, and product event data into one consistent reporting layer across the full funnel from acquisition to retention. Focus areas Marketing & Attribution Analytics • Tools: GA4, Meta, Google Ads, TikTok, pixels, Meta Conversions API, Google Tag Manager, server-side tracking, BigQuery, Power BI, Looker • Techniques: UTM governance, click-ID stitching, session-to-order joins, multi-touch and last-touch attribution, campaign and creative analysis, custom funnel tracking • Outcome: Clear views of channel contribution, campaign efficiency, and customer acquisition performance Funnel, Pipeline & Conversion Analytics • Tools: GA4, CRM systems (HubSpot, GoHighLevel, PipeDrive, etc.), SQL, dbt, cloud warehouses, BI dashboards • Techniques: Funnel modeling from first touch to revenue, lead-to-opportunity tracking, conversion rate decomposition, cohort-based funnel analysis • Outcome: Visibility into where prospects drop off, what converts, and which segments drive the highest-value revenue Product & Growth Analytics • Tools: Mixpanel, Amplitude, GA4, product event tracking, SQL, dbt, cloud warehouses, BI tools, Segment, RudderStack • Techniques: Activation metrics, retention and cohort analysis, feature usage tracking, lifecycle segmentation, product-to-revenue linkage • Outcome: Clear understanding of how product behavior impacts conversion, expansion, and long-term customer value RevOps & Go-To-Market Performance • Tools: HubSpot, Salesforce, Stripe, SQL, dbt, cloud warehouses, Excel • Techniques: Pipeline modeling, revenue timing logic, forecast vs actuals, customer segmentation by channel and product • Outcome: Unified views of pipeline health, bookings, revenue, churn, and growth efficiency across the go-to-market engine Data Modeling & Metric Layer • Tools: SQL, dbt, star schemas, semantic layers, Excel for validation • Techniques: Dimensional modeling, KPI definitions, metric governance, reconciliation across marketing, product, and revenue data • Outcome: Consistent metrics such as CAC, LTV, payback, activation, retention, and growth efficiency across all dashboards Dashboards & Automation • Tools: Power BI, Tableau, Looker, Python, Airflow, cloud warehouses (AWS, Azure, GCP) • Techniques: Automated pipelines, incremental models, QA checks, self-serve dashboard design for growth teams • Outcome: Decision-ready marketing, funnel, and executive dashboards that replace manual reporting Engagements range from ongoing growth analytics support to attribution builds, funnel and product analytics projects, and full reporting audits, all focused on giving teams a single, trusted view of how marketing and product actually drive revenue.

Extensive experience (16 years) in Oracle, MySQL, SQL Server, Postgres, Snowflake and Azure Data Lake methodically identifying and resolving complex underlying causes of problems, using a vast variety of techniques and tools. I have solved numerous show-stopping Performance problems, as well as often re-engineered immensely complex designs and code, providing significantly improved performance. Have designed data warehouse and implemented ETL pipeline strategies on AWS and Azure. Extensive experience as a Data Engineer with multiple work experience in data extraction, data transformation, data load, data protection, data cleansing, data migration, data mergers etc. Expert level ability with Data Architecture, Data Modelling and Data Analysis. I can conceptualize, design and develop long-term, automated, integrated solutions with a focus on increasing your competitive advantage. Have also held roles where I had to work with business end users to provide Solution Architecture and drive the solution from discussing with the users to delivering the final solution product to the end users. Have around 6 years of experience in Python (ETL and Data Analytics), 4 years in Tableau, 2.5 years in DBT and 2 years in Matillion (ETL). Domain expertise: Freights and Logistics (Quotation, Pricing, Booking, Reservation, Inventory management, Operations, Control products for Accenture Freights and Logistics Solutions) - 7 years Finance - Capital Market (Backend book-keeping for different instruments for BNP Paribas) - 3. years Digital Marketing (Generic product for Call Center and Website for a Digital Marketing company called Candid Maven) - 2 years Merchant Data Platform (Creating the automated framework from scratch to bring in data that was managed in Smartsheet to the centralized database using Python and PL/SQL to serve the analytic needs - for a company called Woflow that holds 96% of the market in this domain) - 6 months Pharmaceutical (Data Lake and Data Warehouse setup for Precision for Medicine - integrated systems like CRM (Saalesforce), ERP (Infor CloudSuite, PSA), HR (Greenhouse, ADP, PSA, SAP Success Factor), RM (Smartsheet, WorkFront), Clinical vendor data (Citeline, KMR) - 3 years At Precision for Medicine, I have worked on integrating the data of all the above mentioned disparate data platforms in 1 single dimension model (ERP, HR, RM, CRM) for creating the centralized enterprise analytics platform. I am eager to work with you, to provide reliable, consistent, and High-Level solutions to design/development challenges. Please contact me, so we can discuss how we can work together to FULLY meet your Business Needs!

With 7+ years of experience, I'm Expert in Web Scraping, Data Engineer, AI/ML and Full-Stack Developer specializing in large-scale data extraction, automation, and pipeline engineering. I build robust, scalable systems that transform raw data into actionable insights. 💡 Core Expertise Web Scraping & Automation: Expert in bypassing anti-bot systems (CAPTCHA, rate limits, IP rotation) using Scrapy, BeautifulSoup, Selenium, Playwright, and rotating proxies. Automation & Workflow Engineering: Airflow, Prefect, Dagster, n8n, Zapier, Make, Power Automate, UiPath, Step Functions, Logic Apps, GCP Workflows, Business Process Automation, RPA, CI/CD, Jenkins, GitHub Actions, GitLab CI/CD, Monitoring & Alerting. Data Engineering: Designing and building scalable ETL/ELT pipelines for structured, semi-structured, and unstructured data using Apache Airflow, Apache Spark (PySpark), Pandas, Dask, Databricks, Snowflake, Apache Kafka, Apache Hive, Apache Hadoop, Delta Lake, Apache Iceberg, dbt, AWS Glue, Azure Data Factory, Google Cloud Dataflow, Apache NiFi, Trino, Presto, and Apache Beam. Experienced in data warehousing, data lakes, lakehouse architectures, data modeling, data transformation, data quality, data governance, batch and real-time processing, streaming data pipelines, orchestration, workflow automation, schema design, partitioning, optimization, and performance tuning. Proficient with cloud platforms including AWS, Azure, and GCP, S3, Redshift, EMR, Athena, Lambda, Azure Synapse Analytics, Azure Data Lake Storage, BigQuery, Cloud Storage, and Pub/Sub. Skilled in SQL, Python, data integration, data migration, CDC, metadata management, monitoring, CI/CD, Docker, Kubernetes, and modern data stack technologies. Backend Development: High-performance APIs and microservices with FastAPI, Django, Flask, and Celery for async task handling. AI/ML Integration: Leveraging NLP and LLMs (LangChain, Llama, NLTK) for data enrichment, classification, and intelligent automation. Cloud & DevOps: Deploying scalable scrapers and data workflows on AWS (Lambda, ECS, S3), GCP, Docker, and Kubernetes. 🛠️ Tech Stack Data & Scraping: ▸ Scrapy | Selenium | Playwright | Proxies (BrightData, ScraperAPI, etc) ▸ Pandas | PySpark | Apache Airflow | PostgreSQL | MongoDB | Redis Backend & Cloud: ▸ Python (FastAPI, Django, Flask) | Celery | RabbitMQ ▸ AWS (Lambda, ECS, RDS, S3) | GCP | Docker | Kubernetes AI/ML: ▸ NLP (NLTK, spaCy) | LLMs (LangChain, OpenAI, Llama) | Data Annotation Let's turn your data challenges into reliable, scalable solutions. Send me a message to discuss your project!