Architect and scale next-generation big data ecosystem.
Leverage Databricks to design robust ETL pipelines, implement sophisticated data models, and integrate diverse streaming and API sources.
Bridge the gap between complex engineering requirements and actionable business insights.
Ensure high-performance and compliance of data infrastructure.
Build and maintain high-performance, scalable ETL/ELT pipelines.
Architect robust integrations across ecosystem, including APIs and databases.
Implement data transformation logic, data enrichment, and cleansing protocols.
Develop high-efficiency data models and schemas, maximizing query performance.
Oversee and optimize cloud-based infrastructure using containerization and distributed computing.
Empower Machine Learning initiatives and collaborate with Data Science teams for predictive models.
Design and implement Zero-Touch automation for CI/CD.
Execute data governance, lineage tracking, and access controls.
Maintain comprehensive technical documentation.

6+ years of proven experience architecting and developing enterprise-scale data solutions.
Extensive hands-on experience with the Azure Data Stack, including Synapse, Data Factory, Databricks, CosmosDB, and Azure SQL.
Expert-level command of SQL and Python (required); additional proficiency in JavaScript, R, VBA, or web technologies (HTML/CSS/JSON) is highly valued.
Demonstrated success in building and managing complex ETL/ELT pipelines within both Databricks and modern Business Intelligence environments (e.g., Power BI, Sisense, Tableau, or Domo).
Deep experience leveraging API calls to ingest, synchronize, and automate data flow between disparate third-party and internal systems.
Ability to bridge the gap between backend data engineering and front-end visualization, specifically optimizing Power BI for high-performance reporting.
A track record of designing, testing, and scaling automated data systems that drive operational efficiency, measurable cost savings, and improved business outcomes.
Experience working directly with business partners to translate high-level goals into technical workflows that enhance decision-making.

Data Engineer

Key skills