Design, build, and support high-quality data solutions and pipelines using modern engineering practices and tools.
Partner closely with product managers, software engineers, and data analysts to deliver scalable, reliable data capabilities that power digital products and business insights.
Accountable for the end-to-end lifecycle of data products, from design and implementation through production support, data quality, and performance against key metrics.
Integrate data from diverse sources including APIs, databases, event streams, and third-party systems.
Apply modern engineering practices, including version control, testing, CI/CD, and automated deployments.
Ensure data quality, integrity, and reliability through validation, monitoring, and observability tools.
Optimize data workflows for performance, cost efficiency, and operational resilience.
Document data flows, lineage, and technical components in support of transparency and maintainability.

Strong proficiency with data pipeline development in Python, Java, or Scala.
Experience with modern data frameworks (Spark, Kafka, Flink, dbt, or equivalent).
Solid understanding of SQL and NoSQL databases and data modeling principles.
Ability to optimize SQL, pipelines, and storage for performance and cost.
Experience building batch and/or streaming data solutions.
Experience using Microsoft Fabric Notebooks to develop, debug, and operationalize data engineering workflows.
Experience with containerization and orchestration tools (Docker, Kubernetes).
Experience with observability and monitoring tools (Datadog preferred).
Ability to work in collaborative, iterative, product-centric team environments.
Strong communication and problem-solving skills.
4 year Bachelor's Degree.
3 or more years of experience (Preferred)

Senior Data Engineer

Key skills