Senior Data Engineer

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.