Senior Data Engineer

This is a three months remote job to begin

We are seeking experienced Data Engineers to support the design, development, testing, deployment, and operationalization of analytics-ready data models and associated data pipelines. These engineers will work as an extension of the existing engineering organization and execute work from a jointly prioritized backlog.

Key Responsibilities:

• Design logical and physical data models.
• Develop analytics-ready Tier-2 data models using dimensional modeling and star-schema principles where appropriate.
• Define facts, dimensions, relationships, measures, and transformations.
• Develop ingestion, transformation, and orchestration pipelines.
• Implement batch and streaming data-processing workflows.
• Support data replication and historical backfills.
• Develop data-quality controls and validation logic.
• Perform unit, integration, regression, and data-quality testing.
• Reconcile source and target datasets.
• Prepare production-ready code, configuration, and models.
• Participate in code reviews and approved release processes.
• Support production deployment and post-deployment validation.
• Troubleshoot defects and perform root-cause analysis.
• Create technical documentation, release notes, and operational materials.
• Participate in daily stand-ups, design reviews, demonstrations, and knowledge-transfer activities.

Required Qualifications:

• Five or more years of professional data engineering or distributed-systems experience.
• Strong production experience with batch and streaming data architectures.
• Experience building and maintaining production data pipelines.
• Experience with dimensional data modeling and star-schema design.
• Strong programming skills using Python, Java, and SQL.
• Experience with data quality, automated testing, and production troubleshooting.
• Experience with source control, CI/CD, code reviews, and agile engineering practices.
• Ability to work effectively within a distributed global engineering team.

Required Technologies:

Apache Iceberg, Apache Airflow, Apache Spark, Apache Kafka, Apache Flink, Snowflake, Java and Python, Amazon Web Services, SQL and data modeling

• Expected Deliverables
• Completed source code, configurations, and data models.
• Technical and operational documentation.
• Approved pull requests.
• Testing and validation evidence.
• Engineering demonstrations or technical walkthroughs.
• Release notes and change summaries.
• Production deployment artifacts.
• Post-release validation.
• Knowledge transfer and documented handoff of remaining work.