Hire the Best Big Data Engineers
in Germany

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.

ABOUT ME I have been working in the field of Big Data for more than 6 years during which I've gained hands-on experience with Spark, Hive, HDFS, YARN, Apache Livy, HBase, HiFi, Airflow, Docker, Kubernetes, MQTT, and more. Most often I use Scala, Python, and SQL programming languages, and I also have a basic knowledge of C/C++, Go, Java, Kotlin, and R. I have been using Azure, AWS, Digital Ocean, and Databricks cloud providers. I have practical experience in all phases of product implementation: initiation, research, requirement definition, design, establishment of milestones, development, integration, testing and further support. I have experience in firefighting with a highly loaded data processing system. I play an active and constructive role within the team. After some time, I've become a good connoisseur of business model and business field, which allows me to share knowledge among team members. INDUSTRY EXPERTISE Telecommunication, Mobile Games, User Acquisition, Retail, Logistics. OPEN SOURCE CONTRIBUTIONS Im trying to contribute to open source whenever i have some free time. GitHub: @ostronaut

I architect data platforms for companies where bad data isn't a reporting problem — it's a regulatory risk, a compliance failure, or a million-dollar pipeline outage. My clients include Novo Nordisk, Danske Bank, 10XCRM and enterprise companies across maritime, e-commerce, and SaaS. I've worked alongside AWS Professional Services on mission-critical cloud migrations and built AI systems that are running in production today — not proofs of concept. Why Me: You're not getting a pipeline developer. You're getting the person who decides what gets built, how it scales, and why it won't break at 3 AM. I've designed systems processing 60M+ events/day, migrated 8 billion records with zero data loss, and replaced 6-8 hour manual workflows with 30-minute automated pipelines. Recent engagements → Novo Nordisk — Event-driven scientific intelligence platform on AWS. Ingesting research documents from 6+ sources (PubMed, Springer, BioArxiv) through a Bronze/Silver/Gold lakehouse architecture. MSK Kafka with 10+ topics, Iceberg tables, OpenSearch, DynamoDB caching layer. Processing 30M+ events/day and 4TB+ monthly. → Danske Bank — Enterprise cloud migration alongside AWS Professional Services. Architected ETL pipelines for metadata integration covering VMs, storage, databases, and wave planning. Built Python automation that replaced Excel-driven migration processes — 6-8 hours down to 30 minutes. Also developed an EC2 recommendation engine for optimal instance sizing. → Maritime AI — AI-powered document processing for the maritime industry. Extracts maintenance plans, spare parts, and BOM data from complex S1000D technical manuals. RAG system with PDF citation traceability and ERP integration. Deployed on-prem for data sovereignty requirements. → E-commerce brand (Hamburg) — Full Redshift to Snowflake migration. Converted hundreds of legacy SQL Jinja pipelines to Snowflake dialect. Implemented Time Travel, Zero-Copy Cloning, and automated warehouse scaling. Zero downtime during cutover. → 10xCRM (B2B SaaS) — Multi-tenant CRM analytics on GCP. Airbyte, dbt, BigQuery, Looker Studio. Replaced an 8-hour Airbyte sync with a custom Python pipeline running in 12 minutes on Cloud Run. Scales from 1 to N customers automatically. → Jimdo (4.5 years) — Led the Redshift to Snowflake migration handling billions of daily events. Transformed 500+ legacy ETL jobs into dbt models. Integrated data streams from HubSpot (7M+ records), Facebook, Google AdWords, Zendesk, and Stripe. Achieved 60-70% ETL performance improvement through a 3-phase optimization strategy. What every engagement includes: → Architecture-first approach. I design the platform before writing code — lakehouse layers, governance model, cost projections, scaling strategy. You get a blueprint, not just scripts. → Production-grade deliverables. Proper error handling, monitoring, alerting, and documentation. Not notebook code pushed to production. → Knowledge transfer. Your team can maintain and extend everything I build. I don't create dependency. → One week post-deployment support included. Stack: Python, PySpark, dbt, Airflow, AWS (S3, Glue, MSK Kafka, Bedrock, Lake Formation, Lambda, Redshift, EMR, ECS), Snowflake, Databricks, GCP BigQuery, Docker, Kubernetes, Terraform, RAG/LLM integration. Background: Erasmus Mundus MSc in Big Data (UPC Barcelona, ULB Brussels, UFRT France). AWS Certified Data Engineer Associate and AI Practitioner. 10+ years across pharma, banking, energy, maritime, telecom, and SaaS. Based in Hamburg, Germany.

I’m a senior data engineer/solutions architect with a rigorous background in mathematical physics and over $70,000 earned on Upwork. I build production-grade lakehouse platforms, scalable ELT/ETL, and ML/MLOps—with deep, hands-on experience in Google BigQuery and Azure Databricks. I’ve delivered in both enterprise (EY-Parthenon, PwC, Amazon) and startup environments, combining Fortune-500 reliability with startup speed and pragmatism. Why clients hire me: - BigQuery at scale (fast & cost-efficient). Designed serverless ELT on BigQuery + dbt with CI/CD that cut processing costs by ~5× and powered near-real-time marketing analytics (GA4, Google Ads, Facebook Ads, Bing Ads, Shopware) in Looker Studio. - Healthcare & interoperability on Azure Databricks. Built an openEHR-driven research data platform on Azure Databricks, standardized multi-team deployments with Databricks Asset Bundles (DABs), and enforced Unity Catalog governance (RBAC + row filters). End-to-end MLOps with MLflow/Model Registry for risk models. - Enterprise-grade warehousing & CI/CD. Parameterized Synapse deployments; incremental ELT from SAP/CRM APIs with pagination/parallelism—runtime reductions ~5×. - Analytics acceleration. Improved Power BI refresh/report performance ~6× via Azure SQL tuning plus robust ADLS + ADF pipelines with CI/CD. - Proven Upwork delivery. Long-term API integration & data engineering: $44,246.67 on a single engagement (consistent 5★ track record across projects). Core services - BigQuery & GCP: Serverless ELT/ETL with dbt, Cloud Functions, Dataflow; marketing/CRM ingestion to BigQuery; cost/perf modeling; near-real-time dashboards (Looker Studio). - Azure & Databricks: Lakehouse (medallion), Unity Catalog governance, Synapse warehousing, ADF (schema drift/SCD), MLflow MLOps, DABs for IaC. - Interoperability & APIs: HL7 ↔ FHIR ↔ openEHR, REST integrations (SAP/CRM), Ads/GA4 pipelines, Google Apps Script/Node.js. Selected project highlights (Upwork & enterprise) - $44K+ long-term API integration & data engineering (Apps Script + Node.js). - BigQuery marketing & analytics stack: multi-channel ingestion, dbt modeling, CI/CD; costs down ~5×, near-real-time dashboards. - Azure lakehouse & MLOps: openEHR data hub on Databricks with DABs + Unity Catalog; MLflow-driven pipelines. - E-commerce data warehouse: end-to-end build with ML features (k-means, ARIMA/LSTM) for decision support. Certifications - Databricks Certified Data Engineer Professional - Microsoft Certified: Azure Data Engineer Associate (DP-203) - GCP coursework: Big Data & ML fundamentals / modern data warehousing Toolbox - Languages: SQL (advanced SPs/windowing/dynamic SQL), Python (pandas/PySpark/FastAPI), Spark - GCP: BigQuery (advanced), Cloud SQL, Dataflow, Cloud Functions - Azure: Synapse, ADF, ADLS Gen2, Unity Catalog, Purview, Fabric - Databricks: DABs, Workflows, MLflow, Lakehouse governance - Orchestration: dbt (advanced macros), ADF (schema drift/SCD), Airflow (basic) - Visualization: Power BI, Looker Studio, Superset, Tableau

I’m Ekaterina, a Junior Big Data Engineer based in Berlin with a Master’s degree in Engineering Science. My focus is on data processing, analysis, and building reliable data workflows. Skilled in Python, SQL, and modern data engineering technologies, I design and automate efficient data solutions with a structured, detail-oriented mindset. Fluent in English, German, and Russian, and motivated by solving technical challenges with clarity and precision.

I am a seasoned Data Engineer and Big Data Specialist with over 7 years of experience in building and optimizing scalable data pipelines, crafting real-time analytics solutions, and leveraging cloud technologies to deliver business value. My expertise spans across Big Data Ecosystems, Cloud Platforms, and Data Warehousing, ensuring end-to-end solutions for data-driven decision-making. 𝗗𝗼𝗺𝗮𝗶𝗻 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲 : 𝗣𝗵𝗮𝗿𝗺𝗮𝗰𝗲𝘂𝘁𝗶𝗰𝗮𝗹 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 – Extensive experience in clinical data management, working with IQVIA, Sanofi, and optimizing study data pipelines for pharmaceutical research and trials. 𝗙𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗦𝗲𝗰𝘁𝗼𝗿 – Expertise in the insurance domain, handling claims processing, policy data management, and ensuring compliance with industry regulations. 𝗥𝗲𝗰𝗿𝘂𝗶𝘁𝗺𝗲𝗻𝘁 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 – Worked with job advertisement data, company insights, geographical talent search, and salary analytics to enhance recruitment strategies. 𝐊𝐞𝐲 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: Extensive experience in Big Data Analytics, specializing in Apache Spark, Kafka, NIFI, and Databricks, with a strong focus on Delta Lake, Streaming, and Batch Processing. Proficient in building robust ETL/ELT pipelines and designing OLAP data models using technologies Redshift, Snowflake, and BigQuery with dbt transformation. Hands-on expertise in AWS (Glue, S3, EMR, Lambda, Step Functions) and Azure (Databricks, ADF, CosmosDB) to build scalable, cloud-native architectures. Experienced in Docker containerization and deploying distributed applications across various environments. Adept at orchestrating data pipelines with Apache Airflow, Jenkins, and automated CI/CD workflows to streamline production deployments. Skilled in programming with Python and Pandas, with exposure to Scala for efficient data transformation and processing. 𝐋𝐞𝐚𝐝𝐞𝐫𝐬𝐡𝐢𝐩 & 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧: Proven track record in mentoring and leading technical teams, ensuring high-quality deliverables and fostering innovation. Experienced in collaborating with cross-functional teams, translating complex requirements into scalable solutions, and ensuring alignment with business goals. Passionate about adopting Agile (Scrum) and DevOps methodologies to enhance development efficiency and team collaboration. 𝐖𝐡𝐲 𝐂𝐨𝐧𝐧𝐞𝐜𝐭 𝐖𝐢𝐭𝐡 𝐌𝐞? I thrive on solving complex data challenges, driving impactful insights. Whether it’s optimizing data architectures, building real-time analytics solutions, or mentoring teams, Let’s connect and discuss how we can shape the future of data together!