Data Engineer

Description We are looking for a Data Engineer to join a team in Santa Monica, California on a Long-term Contract assignment. This position focuses on building dependable data solutions that connect multiple sources, support reporting needs, and improve access to trusted business information. The role offers a blend of pipeline development, dashboard ownership, data quality work, and cross-functional collaboration with partner teams.

Responsibilities:

• Design, validate, and release data pipelines that bring together information from varied source systems within an existing ingestion environment.

• Create and support connections to external platforms, APIs, and vendor tools so data remains current, consistent, and available for analysis.

• Oversee daily pipeline health, investigate processing issues, and partner with senior engineers to address failures and improve reliability.

• Develop and maintain roughly 10 business intelligence dashboards used by 2 to 3 stakeholder groups, keeping reporting useful and aligned with team needs.

• Improve dashboard quality by reviewing accuracy, optimizing performance, enhancing usability, and retiring reports that no longer provide value.

• Write and maintain data validation checks, including tests at the source level to strengthen data quality and reduce downstream issues.

• Support data modeling and transformation efforts using dbt to prepare clean, well-structured datasets for analytics and reporting.

• Handle ad hoc data requests submitted through an intake process, providing timely answers to business questions with clear supporting analysis.

• Produce and update documentation for pipelines, reporting assets, and operational workflows to promote maintainability and knowledge sharing.

• Take part in peer code review by submitting thoughtful feedback and incorporating suggestions to maintain strong engineering standards. Requirements • 1 to 3 years of experience in data engineering, analytics engineering, or another data-centric technical role.

• Strong SQL skills with the ability to query, transform, reconcile, and validate complex datasets.

• Working knowledge of Python for data processing, automation, or engineering tasks.

• Experience with BI and reporting platforms such as Power BI, Tableau, Looker, Sigma, or comparable tools.

• Familiarity with cloud data warehouse technologies, including Snowflake, Redshift, or similar environments.

• Exposure to dbt and modern transformation practices, or a demonstrated eagerness to learn quickly.

• Understanding of version control workflows using Git.

• Experience with technologies such as Apache Spark, Hadoop, Kafka, and ETL processes is beneficial.

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