Data Engineer

Remote contract for 3 months. Regular business hours.
Position Overview
We are seeking six 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.

Work arrangement
Yes