Hire the Best Big Data Engineers
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👋 Hi, I’m a 🏆 ⭐️⭐️⭐️⭐️⭐️Top Rated Python Data Engineer & Data Visualization Expert at GroupBWT - a 100+ person data engineering company and official AWS, Snowflake & Databricks partner, building enterprise data systems since 2009. As a Python Big Data Engineer, I specialize in designing scalable data systems. My role as a Big Data Engineer is focused on building reliable pipelines, automation, and analytics infrastructure. Every Python Data Engineer decision I make is oriented toward scalability, performance, and data reliability. I work as a Big Data Engineer and Python Data Engineer on enterprise-grade systems where architecture matters for both ingestion and transformation layers. As a Data Engineer, I ensure that raw data becomes structured, usable, and ready for business intelligence. Here’s how I support our clients as a Python Big Data Engineer: ✅ Our ETL pipelines process over 100 million records monthly across major cloud data warehouses
 ✅ My solutions reduce manual reporting effort by up to 80% through end-to-end automation
 ✅ We build Python Data Engineer workflows for integrating and transforming complex datasets ✅ Every pipeline is tested and quality-checked to meet enterprise data standards 🔁 What I Do as a Python Azure Data Engineer and azure data engineer ⚙️ Data Engineering (Python AWS Data Engineer Core Work) 🔹 API & event-based ingestion using Python Data Engineer best practices 🔹 Python + SQL transformations 🔹 Data modeling, schema design, enrichment 🔹 ETL/ELT into Snowflake, Databricks, BigQuery with Python Data architecture 🔹 Monitoring, retries, observability & data quality testing for Python Data pipelines 🔹 CI/CD for pipelines & cloud cost optimization as a Python Data Engineer Platforms I’ve delivered as a Python Data Engineer process 100M+ records/month, integrate 30–80+ APIs, and power real-time BI environments. 📊 Data Visualization & BI (Python gcp Data Engineer Perspective) 🔹 I bridge raw data with business decisions as a Python gcp Data Engineer 🔹 Power BI, Looker Studio & Tableau dashboards connected by Python GCP Data Engineer pipelines 🔹 Executive KPI reporting built by a Python AWS Data Engineer 🔹 Semantic layer & metric standardization in Python Data Engineer systems 🔹 Real-time reporting (<5 min latency) enabled by Python Data Engineer architecture 🔹 BI performance optimization from a Python Data Engineer point of view 🔹 Data storytelling for leadership & operations powered by Python Data Engineer workflows My solutions as a Python Data Engineer reduce manual reporting effort by up to 70-80% and significantly improve forecasting accuracy. 🧩 Recent Experience (Python Data Engineer and Machine Learning Projects) 🔹 Retail & eCommerce Data Warehousing (Python Data Engineer) Built ingestion + normalization pipelines for 120+ eCommerce sources, syncing ~500K SKUs/day into Snowflake / BigQuery using Python Data Engineer architecture. 🔹 FinTech Ingestion & Reporting Layer (Python Data Engineer ) Delivered automated pipeline pulling from 30+ sources (APIs, DBs, files), built with Python Data Engineer logic for validation, transformation, and reporting. 🔹 Government ETL & Document Processing (Python Azure Data Engineer | Data Analyst) Automated processing of 10K+ documents/day using Python Azure Data Engineer workflows and Machine Learning: extraction, classification, mapping, and database loading. 🔹 Healthcare Data Normalization & Compliance (Python AWS Data Engineer | Data Analyst) Cleaned millions of records using Python AWS Data Engineer pipelines with Machine Learning, schema mapping, PII-aware handling, and reproducible transformations. 🔹 Large-scale Cloud Migrations (Python Data Engineer | Data Analyst) Migrated legacy systems into BigQuery/Snowflake using Python Data Engineer architecture with Machine Learning, incremental loads and automated pipelines. 💻 Tech Stack (Python Data Engineer | Data Analyst Toolkit) ⚙️Languages: Python, SQL, DAX, Power Query, PySpark, Scala, Bash/Shell, JavaScript, etc.
 ⚙️Data Engineering & Processing: PySpark, dbt, Airflow, Prefect, CDC, REST & GraphQL, etc.
 ⚙️Data Warehouses & Databases: Snowflake, Databricks, BigQuery, AWS, PostgreSQL, MSSQL
 ⚙️Cloud Platforms: AWS: S3, Glue, Lambda, CloudWatch, Athena, Redshift, BigQuery, Dataflow
 ⚙️Data Modeling & Architecture: Star schema, Snowflake schema, Lakehouse architecture, etc.
 ⚙️Monitoring & Data Quality: dbt, Prometheus, Grafana, AWS CloudWatch, GCP Monitoring, etc.
 ⚙️BI & Visualization: Power BI (Desktop, Service), Tableau, Looker Studio, Metabase, etc.
 ⚙️DevOps & CI/CD: Git, GitHub, GitLab CI, Docker, Terraform, etc. 🚀 If you need automated pipelines, clean data models, and executive-level dashboards - as a Python Data Engineer and Data Analyst I can help you build a robust system from end to end. ➡️ Invite me to your job and let’s design a scalable data strategy with a Python Data Engineer leading the way. Last updated June 15, 2025

I build the clean, reliable data layer your team — and your AI tools — actually trust. From marketing, finance & CRM warehouses in BigQuery to real-time pipelines running at 200k+ events/sec, I've spent 15 years making data fast, accurate, and cost-effective. Most "data problems" aren't really about tools — they're about numbers finance can't trace, dashboards that silently break, and cloud bills that climb faster than the data does. I fix the layer underneath so the whole thing just runs — and often cut the bill while doing it. ⎯⎯⎯ What I do for you ⎯⎯⎯ ◆ Modern Warehouses in BigQuery (dbt + Medallion) — Unified, documented, AI-ready data from ad platforms (Meta, Google, TikTok), CRMs, and ERPs. For enhanza I consolidated financial data from 1,000+ organizations into one BigQuery platform with self-serve dashboards. ◆ AI-Ready & LLM Pipelines — Data modeled so your AI tools consume it directly: LLM enrichment/categorization, clean context windows, no manual prep. Shipped code-first with Claude Code + gcloud — no hand-written SQL in the console. ◆ Cut Your Cloud Bill (FinOps) — Runaway AWS costs are usually egress fees and over-priced managed services, not the data itself. I migrated a client's Dagster pipelines from AWS to Civo Kubernetes + Cloudflare R2 — eliminating S3 egress fees and slashing managed-cluster costs, with no orchestration rewrite. If your bill is climbing, I'll audit it and re-architect the expensive parts. ◆ Real-Time & High-Scale (when you need it) — Streaming in Flink/Kafka and sub-second OLAP in ClickHouse/StarRocks. I've run 200k+ ingest events/sec in an air-gapped cluster — so a standard pipeline is routine for me. ◆ Reliability & Observability — Monitoring, lineage, and schema-drift alerts so dashboards stop breaking. On one platform this cut data downtime by ~90%. ⎯⎯⎯ How I work ⎯⎯⎯ ▹ Root-cause, not patches. I fix the layer underneath so the same dashboard doesn't break again next month. Quick patches are how data platforms rot. ▹ Built to run without me. No "works once on my laptop" scripts — proper deployment, secrets, logging, alerts, and infrastructure as code (Terraform). Reproducible, and yours to keep. ▹ Straight about what I know. If something's outside my wheelhouse, I say so up front and give you the honest trade-off. I won't learn on your budget and call it experience. ▹ I own the outcome. Give me the goal and I'll work through the ambiguity and keep you posted — no micromanagement needed. ▹ A full team behind me. I run with a ~20-person team across data engineering, BI, DevOps, and AI/ML — so you're never betting on one person's calendar or blind spots. You work with me directly, and I pull in the right specialist when the scope calls for it. Senior ownership, agency depth. ⎯⎯⎯ Tech I work in daily ⎯⎯⎯ ▹ Warehouse & Analytics: BigQuery, dbt, dlt, Meltano, Medallion Architecture, Power BI, Looker Studio, Metabase ▹ Cloud & Orchestration: GCP, AWS, Azure, Civo, Airflow, Prefect, Dagster, Kubernetes, Terraform ▹ Streaming & Performance: Kafka, Flink, Spark/PySpark, ClickHouse, StarRocks, Iceberg, Delta, Polars, Cloudflare R2 ▹ AI-first delivery: Claude Code + gcloud/CLI, LLM enrichment pipelines ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯ I don't just "install tools" — I design for compute cost (FinOps) and data reliability. If your cloud bill is climbing or your reporting can't be trusted, I'll audit the stack and tell you exactly what to fix. Want a quick, no-pressure look at your setup? Send me a message and I'll share where I'd start.

👋 I am new to Upwork, but not new to the work. I have 8+ years of real production experience, and I take every project seriously. I build data systems, AI pipelines, and automation workflows that work reliably at scale.😎 I am a Senior Data Engineer and AI Integration Specialist with 8+ years of experience. I do not just move data from one place to another. I design systems that turn complex and messy data into clean, useful information and build automation that saves teams hours of manual work every week. 🧠 Tech stack: Python, SQL, PySpark, AWS, Snowflake, BigQuery, Databricks, PostgreSQL, Airflow, dbt, Docker, FastAPI, n8n, Claude API, OpenAI, LangChain, Playwright, Supabase, Airtable, Salesforce, GoHighLevel 💡 What I bring: • Pipelines that process 100M+ records every month • Up to 70–80% reduction in manual reporting • AI and LLM integrations that automate real business workflows • Web scraping systems that collect and enrich data at scale • Strong focus on data quality, testing, and stability • Solutions that are easy to support and scale ⚙️ What I do: • Build data pipelines from APIs, databases, and files • Design data models and warehouse architectures • Work with cloud platforms: AWS, BigQuery, Snowflake, Databricks • Set up orchestration with Airflow, Prefect, and dbt • Build AI agents and RAG systems using Claude and OpenAI APIs • Automate workflows with n8n, Make, and custom Python scripts • Build web scrapers with Playwright, Scrapy, and BeautifulSoup • Integrate CRMs: Salesforce, HubSpot, Airtable, GoHighLevel • Create dashboards in Power BI, Tableau, Looker, Metabase, and Retool Experience: ▶️ eCommerce: 100+ data sources, product datasets, marketplace integrations ▶️ FinTech: data pipelines, financial reporting, regulated environments ▶️ Healthcare: data cleaning and structuring for analysis and reporting ▶️ Real Estate and PropTech: pricing models, permit data pipelines ▶️ Government: automated document and data processing ▶️ Migrations: legacy SQL and Excel to modern cloud platforms 🚀 If you need reliable data infrastructure, AI automation, or clean analytics, I can help.

I have successfully brought many data-driven web applications from scratch to production. I have the knowledge and track record to bring your data-driven idea to a production-ready level for thousands of users. 

Customers: ✅ Mediengruppe RTL (Biggest German media company) ✅ KPMG 
✅ Marketalerts 
✅ GrowGanic 
✅ Assetclassics Products: ✅ Marketalerts (financial platform) ✅ ABTester (marketing AB-testing reporting platform) ✅ MaretingInsight (custom marketing analytics solution) Unique core skills: ✅ Expert in custom matching algorithms ✅ Expert in data-driven applications ✅ Expert in building scalable architecture Business domain expertise: ✅ Finance 
✅ Cars 
✅ Marketing

✅ 8+ Years as a Data Engineer 📊 Successful Data Engineering Projects Across 22+ Industries in 5 Countries 👨‍💼 Leading a Team of Data Engineers 🌎 Fluent English Hi, I’m Roman — Senior Data Engineer, Data Engineer Consultant, and Enterprise Data Engineer with extensive experience building scalable data platforms, cloud ecosystems, and modern analytics infrastructure. As a Data Engineer, I help companies design, optimize, and modernize enterprise data environments that transform raw information into actionable business intelligence. My background as a Data Engineer covers the full lifecycle of data engineering — including ETL development, cloud migration, data warehouse architecture, real-time processing, and analytics automation. Why Clients Choose Me ⚡ Senior Data Engineer experienced in enterprise-scale ETL and cloud solutions 📈 Data Engineer focused on scalable analytics architecture and performance optimization 🌎 Fluent English communication and stakeholder management 👨‍💼 Lead Data Engineer with experience managing distributed engineering teams 🔍 Business-oriented Data Engineer focused on automation and measurable outcomes Core Expertise Data Engineering & ETL: Azure Data Factory (ADF), SSIS, Apache Spark, Databricks, PySpark, Apache Kafka, dbt Core, Data Pipeline Automation, Data Migration & Transformation, Batch & Real-Time Processing — delivered by an experienced Data Engineer. Data Warehousing & Architecture: Enterprise Data Warehouse (DWH), Lakehouse Architecture, Databricks Lakehouse, OLAP & SSAS, Data Modeling, Data Governance, Azure Synapse Analytics, Snowflake, BigQuery — implemented by a Senior Data Engineer. Databases: Microsoft SQL Server, PostgreSQL, MySQL, Oracle, Azure SQL Database, MongoDB, Neo4j, Redis, SQLite — managed and optimized by a Data Engineer. Cloud Platforms: Microsoft Azure, AWS (Glue, Athena, S3, MSK, EC2, RDS), Snowflake, Office 365 — modern cloud ecosystems built by a Data Engineer. Programming & Analytics: Python, SQL, Power BI, DAX, Power Query, API Integrations, Data Automation — advanced technical expertise from a Data Engineer. 💼 Services I Offer 🛠️ ETL Pipeline Development Data Engineer building scalable ETL/ELT pipelines Data Engineer automating ingestion and transformation workflows Data Engineer optimizing existing processes and infrastructure Data Engineer integrating APIs, SaaS, ERP, and CRM systems 🛠️ Data Warehouse Engineering Data Engineer designing enterprise DWH solutions Data Engineer implementing scalable analytics platforms Data Engineer creating OLAP models and data marts Data Engineer improving governance and data quality frameworks 🛠️ Cloud Data Engineering Data Engineer implementing Azure cloud data platforms Data Engineer leading cloud migration and modernization initiatives Data Engineer designing lakehouse architecture solutions Data Engineer processing big data using Spark and Databricks 🛠️ Data Integration & Automation Data Engineer connecting SQL, APIs, Excel, ERP, and CRM systems Data Engineer automating reporting and workflows Data Engineer configuring orchestration and refresh processes Data Engineer centralizing enterprise analytics ecosystems 🛠️ BI & Analytics Support Data Engineer preparing optimized datasets for reporting Data Engineer improving Power BI data models Data Engineer supporting executive dashboards and KPI tracking Data Engineer increasing reporting scalability and performance As a dedicated Data Engineer, my goal is to help businesses create reliable, scalable, and future-ready data platforms that support analytics, automation, and strategic decision-making. Whether you need a Senior Data Engineer for ETL development, a Cloud Data Engineer for migration projects, or a Lead Data Engineer to architect a complete analytics ecosystem — I can help. 📩 Send me a message and let’s discuss how a Data Engineer can accelerate your business goals.

Hi! I'm a Data Engineer and Data Scientist with over 3 years of experience building scalable data pipelines, cleaning and analyzing complex datasets, and delivering AI/ML solutions that create real business value. I specialize in designing event-driven cloud architectures, developing ETL/ELT pipelines for real-time and batch processing. Whether it's processing terabytes of data or fine-tuning a neural network — I’m all about clean code, solid logic, and measurable impact.