We are looking for a Senior Data Engineer to build and scale a modern, AWS-based data platform powered by serverless pipelines, DuckDB, and Delta Lake architecture. You will work on integrating multiple SaaS and operational data sources into a robust data warehouse used for analytics and Tableau reporting.
This role requires a hands-on engineer comfortable with Python-based data processing, AWS services, and non-traditional data stack components (DuckDB, Polars, etc.).
You will play a critical role in building a robust, production-grade data platform used for analytics, reporting, and future AI use cases.
Key Responsibilities: * Design, build, and maintain ETL/ELT pipelines from multiple data sources: * APIs (e.g., RingCentral, Google Ads, GA4); * Third-party SaaS platforms; * Financial/accounting systems; * Non-standard data sources (custom ingestion); * Develop scalable ingestion frameworks (batch and incremental loads); * Handle complex data transformations, including: * Schema normalization across inconsistent sources; * Historical vs incremental data reconciliation; * Build and optimize data warehouse structures (fact/dimension models); * Ensure data reliability through logging, monitoring, and error handling; * Optimize performance of queries and storage (cost + speed); * Collaborate with Data Architect and BI team to ensure data usability; * Support QA and validation processes; * Document pipelines, data flows, and system architecture.
Requirements: * 7+ years of experience in data engineering; * Experience with AWS ecosystem: * Lambda, EC2, SQS, EventBridge, ECR, Glue, Athena; * Strong SQL expertise (advanced level); * Experience with Python (or similar) for data processing; * Hands-on experience with modern data warehouses: * Snowflake / Redshift / BigQuery; * Experience integrating REST APIs and third-party systems; * Strong understanding of data modeling (star schema, normalization); * Experience with orchestration tools (Airflow, Prefect, etc.); * Familiarity with data quality and validation frameworks; * Ability to work with messy, inconsistent, real-world data; * English: Upper Intermediate or higher.
Nice to Have: * Experience with Delta Tables; * Experience with dbt or similar transformation tools; * Experience with marketing data (GA4, Google Ads); * Experience with financial/accounting data; * Exposure to real-time or near-real-time data pipelines; * Experience supporting BI tools (Tableau, Looker, etc.).
We Offer: * Maximum flexibility; * Professional trainings, conferences, and certifications; * Corporate events and benefits; * Professional literature; * English courses.
