Seasoned Data Engineer & Backend Developer with deep expertise in building high-performance, secure, and scalable data platforms for industries like Fintech, Health & Nutrition Tech, Digital Media (Amazon Music), Insurance, and Gaming/Sports Betting. I specialize in Python-driven data architectures on AWS and Azure, enabling real-time analytics, rigorous data quality, and secure data handling for batch and streaming workloads. My solutions turn complex datasets into business intelligence that powers product innovation and regulatory compliance. 🔹 Cloud-Native Data Pipelines – Expert in architecting ELT/ETL workflows using Apache Airflow, DBT, AWS Glue, and Azure Data Factory. 🔹 Streaming & Real-Time Systems – Built Kafka- and Kinesis-based pipelines with schema registry, Spark Streaming, and Azure Event Hubs. 🔹 Secure & Governed Architecture – Implemented granular IAM, end-to-end encryption, metadata lineage (AWS Glue Catalog, Azure Purview), and compliance controls for SOC and HIPAA-style standards. 🔹 Backend & Microservices – Designed modular FastAPI/Flask services, asynchronous job queues (Celery, Lambda), and robust APIs (OAuth2, JWT, API Gateway). 🔹 Data Modeling & Storage Optimization – Skilled in dimensional models, data vaults, and tuning storage engines (PostgreSQL, Redshift, Snowflake, S3/ADLS Lakehouses). 🎧 On Amazon Music, I contributed to scalable event-driven services and analytics pipelines that processed billions of user interactions to drive personalization and reporting. ✅ Let’s work together if you need: Real-time & batch data infrastructure Secure cloud data platforms (AWS, Azure) Streaming data ingestion & CDC (Debezium, Kafka) Optimized data lake/warehouse design Backend services to support analytics and product features 📈 Whether you're building a modern data stack or re-architecting legacy systems, I bring hands-on expertise, architectural clarity, and a delivery mindset.

Berlin-based freelance data engineer helping teams automate reporting workflows, improve data reliability, and fix messy SQL/dbt pipelines. Experienced in building production-grade systems across energy, banking, and AI-driven applications. Core stack: - Python - SQL - dbt - BigQuery - GCP Available for freelance and part-time engagements. I enjoy solving messy operational problems and building reliable systems that reduce manual work for engineering and business teams.

Data Analyst with experience in analysing business performance and operational metrics across digital products and web-based services. Skilled in SQL, Python, and dbt for building analytics-ready datasets. Experienced in statistical analysis, basic machine learning, KPI design, and behavioural segmentation to identify trends, support decision-making, and improve business performance. 𝐈’𝐦 𝐩𝐚𝐫𝐭𝐢𝐜𝐮𝐥𝐚𝐫𝐥𝐲 𝐢𝐧𝐭𝐞𝐫𝐞𝐬𝐭𝐞𝐝 𝐢𝐧 𝐫𝐨𝐥𝐞𝐬 𝐰𝐡𝐞𝐫𝐞 𝐝𝐚𝐭𝐚 𝐢𝐬 𝐮𝐬𝐞𝐝 𝐭𝐨: • Improve service delivery, onboarding, and retention; • Understand user behaviour and operational workflows; • Build reliable data models; and • Support product, operations, and growth decisions. If your team works with behavioural data, digital products, web-based services, or related fields, I'd be glad to connect.

Imagine this: Your company has valuable data, but pipelines are messy, workflows are manual, and analytics are slow. Decisions are made on guesswork instead of facts. The result? Wasted time, missed opportunities, and stalled growth. That’s where I come in. I help businesses build scalable, automated data pipelines that turn raw data into actionable insights—so you can make decisions confidently and efficiently. ✨ WHAT I OFFER: ✔ Design and automation of ETL pipelines that clean, transform, and load your data reliably ✔ Workflow orchestration with Airflow to reduce repetitive tasks and errors ✔ Data modeling with dbt for clean, maintainable datasets ✔ Scalable cloud analytics with Snowflake ✔ Python & SQL scripting for data extraction, transformation, and analysis ✨ EXTENSIVE EXPERIENCE IN THE FOLLOWING: 🔹 Building and automating ETL/ELT pipelines 🔹 Data cleaning, transformation, and integration 🔹 Workflow automation and orchestration 🔹 Data modeling and structuring for analytics 🔹 Cloud data warehousing and scalable storage 🔹 Python & SQL scripting for complex operations 🔹 Creating interactive dashboards and reports ✨ TOOLS & TECHNOLOGIES I USE: 🛠Python (Pandas, NumPy) 🛠SQL (PostgreSQL, MySQL, Snowflake SQL) 🛠dbt for modern data modeling 🛠Airflow for workflow orchestration 🛠 Snowflake for cloud data warehousing 🛠 Power BI & Tableau for dashboards and visualizations I focus on accuracy, automation, and scalability, helping you transform your data into insights that support growth, efficiency, and smarter business decisions.

Hi, nice to meet you! I’m a Data Analytics, Data Engineer, and Cloud Enthusiast experience in build data pipeline and maintain infrastructure in cloud (AWS/GCP) and sometimes design data visualization using streamlit or other BI tools (e.g. powerBI, tableau, metabase) for small and medium-sized business. If you're looking for someone who can utilizing data, find insightful data storytelling, and creating interactive dashboards, I'm eager to provide the best and yet impactful solution. Common project I do: - Design database/data warehouse modeling using SQL | Dbt - Crafting custom and maintainable SQL queries - Crafting scripts to extract and import data from multiple source (e.g. wesbite, excel/pdf/doc, database, API) - Developed interactive data visualization chart using Streamlit and other BI tools (e.g. tableau and powerBI, metabase) - Design and developed architecture for data pipeline (ETL | ELT | Lambda | Kappa Architecture) - Orchestrate data pipeline using Cron Job | Apache Airflow | Kestra | Perfect - Perform data transformation or data cleaning using Pandas | Polars | Apache Spark - Testing for data freshness using Dbt | Soda | Great expectations and Monitoring data pipeline using Prometheus + Grafana - Chunking and processing data into vector database on PostgreSQL | Pinecone - Build automation script using bash, Python | Golang, and YAML - Build automation for Cloud Infrastructure using Terraform Looking forward to have collaborations and working with you!

I’m a data engineer with 4+ years of experience building reliable, production-grade data systems for high-volume, revenue-critical platforms. I specialize in designing end-to-end analytics pipelines, reconciling complex financial and usage data, and turning messy, multi-source datasets into trusted, decision-ready insights. My work spans SQL-heavy analytics, dbt modeling, Airflow orchestration, cloud data warehouses, and robust reporting workflows. I’ve owned pipelines in production, handled edge cases like late-arriving data and reconciliation mismatches, and partnered closely with product, finance, and engineering teams to ensure data accuracy at scale. I value correctness, clarity, and maintainability. If you need someone who can think deeply about data integrity, performance, and long-term system design, I bring both hands-on execution and strong architectural judgment.

Looking for a data professional who understands both the technical complexity and business impact of your data? You've found the right person. With 6 years of hands-on experience and a Master's in Computer Science with AI, I bridge the gap between raw data and strategic business decisions. I've worked across leadership teams in multiple industries, giving me the unique ability to translate technical solutions into business value. 🎯 Industries I've Delivered Results In: • Marketing Analytics – Campaign optimization, attribution modeling, customer journey analysis • Logistics & Supply Chain – Operations efficiency, demand forecasting, inventory optimization • Subscription Businesses – Churn prediction, LTV analysis, retention strategies • Media – Content performance, audience analytics, monetization insights 🛠️ My Technical Arsenal: Cloud Platforms: GCP, Azure, Databricks Data Engineering: BigQuery, DBT, Python, SQL Analytics & BI: PowerBI, Looker, Excel Focus: End-to-end data pipelines, advanced analytics, and business intelligence ✅ Why Choose Me: • Business + Technical Expertise – I don't just build dashboards, I solve business problems • Leadership Experience – I've sat in boardrooms and understand what executives need • Industry Versatility – Proven track record across diverse sectors • Full-Stack Approach – From data engineering to analytics to visualization • Master's in CS with AI – Strong theoretical foundation meets practical application Whether you need to build scalable data infrastructure, uncover hidden insights in your business data, or create analytics that actually drive decisions – I deliver solutions that work in the real world. Ready to turn your data into your competitive advantage? Let's discuss your project. --- Available for both hourly and project-based engagements

Experienced Analytics and Data Engineer with 5+ years of experience in SQL-heavy data analysis, data architecture and modeling, and BI reporting. Skilled at scaling dbt (data build tool) implementation from robust disparate sources. I’m passionate about complex data structures, problem solving, and technical development, with a knack for picking up new data tools and concepts quickly. Whether you're trying to organize and wrangle unruly data, migrate to a modern data warehouse, or convert existing SQL into more modular code, I can help. • Knows dbt, Snowflake, Tableau, and Looker • Full end-to-end project management • I value intentional communication, so let's establish a consistent cadence

Your Go-To Data & Analytics Engineer for Scalable, Cloud-Native Solutions Need someone who can clean up chaotic data, design pipelines that don't break, and turn raw numbers into real decisions? That's where I come in. I engineer end-to-end data solutions using: - GCP & AWS for cloud-native deployments - Airflow, dbt, PySpark, BigQuery, Snowflake for seamless data orchestration and warehousing - Kafka for real-time streaming pipelines - PostgreSQL, MongoDB for robust data storage - Great Expectations for ensuring data quality and trust From building batch/streaming pipelines and handling SCD Type 1 & 2, to modeling clean, analytics-ready layers (Star Schema, 3NF, or Data Vault) — I bring structure, clarity, and business focus to every project. Clients appreciate my no-fluff approach: clear communication, fast turnarounds, and data systems that just work. Let's build a data foundation that scales with your business.

- Certification: Postgraduate Diploma in Big Data Analytics from C-DAC, Noida. - Enthusiastic about tackling challenges and eager to explore new technologies. Possess over 6.5+ years of hands-on experience in product development, technical architect design, big data asset development, big data migration, web application development, and ETL. Demonstrated expertise in offering direction, formulating strategies, and providing a visionary approach in the realm of technology and product development.- Designed and implemented a scalable financial data ingestion and transformation pipeline for multiple business units. Built robust workflows using Apache Airflow, DBT, and Trino, with historical tracking via SCD Type 2. Created reusable SQL models, optimized data access through unit-specific views, and validated schemas against Source-to-Target (S2T) mappings. Enabled efficient storage and querying using Iceberg and Parquet formats on AWS S3, supporting business logic execution and reporting.- Leveraged Airflow as the orchestration service for the backend data ingestion pipeline, optimizing data engineering processes through AWS EMR. Implemented a robust backend pipeline for daily scheduled data ingestion, incremental load & full load harnessing AWS services such as MWAA, EMR, S3, Athena, and RDS (Postgres, MySQL) alongside PySpark and Hive. Orchestrated Managed Apache Airflow (MWAA) to streamline the backend data ingestion pipeline, further enhancing data engineering processes through EMR.- Developed a scalable ML model execution pipeline automating the ML model execution process for each batch of data fetched from the data warehouse (Redshift). Implemented the pipeline with Python, R, Docker, and various AWS services (EMR, ECS, Lambda, SQS, Redshift, MySQL).Established an automated data ingestion flow for clinical data, pulling information from diverse sources, flat files and ingesting it into databases after applying business rules, DQM checks, standardization and SCD2 implementation.- Utilized a diverse technology stack: Python, Databricks, PySpark, DBT, Starburst, Trino, Control M, Hadoop, Hive, Hbase, Airflow, Docker, Kubernetes, Shell Scripting, AWS: EMR, MWAA, SQS, ECS, EKS, ATHENA, GLUE, ECR, EC2, S3, S3 Glacier, ELB, API Gateway, Lambda, CI/CD, PostgreSQL, MySQL, Aurora, Amazon Redshift, Cloud9, CloudWatch, Amazon Managed Airflow, CloudFormation, Auto Scaling, IAM, SNS, SES, Terraform, RESTful API, Flask, FastAPI, GraphQL, GitHub, Bitbucket, SonarQube, AZURE, Elasticsearch & more