Data Engineer
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Job Description
Senior Data Engineer designing and implementing cloud-native data platforms for international clients. Maintaining data flows and building a modern data warehouse for AI/LLM integration.
Responsibilities:
- Design, build, and operate modern, end-to-end, cloud-native data warehouses
- Develop and maintain robust ELT/ETL pipelines that integrate multiple internal systems (servicing, origination, CRM) and third-party data feeds
- Create scalable data models for reporting, BI (semantic layer), and future AI/ML initiatives
- Implement data quality, governance, and security practices aligned with stringent U.S. financial regulations
- Work closely with C-suite stakeholders and directors in the U.S. to translate business requirements into technical data architecture
- Optimize the performance of queries, pipelines, and workflows to ensure efficiency and cost control
Requirements:
- 4 to 7 years of verifiable experience building end-to-end cloud data warehouses
- Microsoft Fabric (highly preferred) OR portable stacks (BigQuery, Snowflake, Databricks)
- Cloud Infrastructure: Azure data stack (Data Factory, Synapse, Fabric) or equivalent on AWS/GCP
- Core Languages: Advanced SQL (dimensional modeling, performance optimization) and Python (transformation, orchestration, scripting)
- BI Tools: Power BI or equivalent (Looker, Tableau, Mode)
- Orchestration and Transformation: Azure Data Factory, Airflow, dbt, Dagster, or similar tools
- Valid US Visa (Minimum B1/B2): Confirmed availability to travel to the US quarterly
- Direct Exposure to Stakeholders: Experience working directly with executives in the U.S.
Benefits:
- Remote work options
- Professional development opportunities
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