Design, build, and maintain robust data pipelines (batch and real-time).
Ingest data from multiple structured and unstructured sources.
Develop and optimize ETL/ELT workflows using dbt.
Ensure data quality, integrity, availability, and security across platforms.
Collaborate with analytics, data science, and product teams to understand data requirements.
Model data for analytics star and snowflake schemas.

🎯 Requirements

8+ years of experience in data engineering with CS or engineering degree or equivalent.
Strong SQL proficiency and experience with relational and NoSQL databases.
Hands-on with data processing frameworks Spark or Flink or similar.
Proficiency in Python, Java, or Scala.
Experience building data pipelines using orchestration tools like Airflow or Dagster.
Hands-on with dbt for developing analytics-ready data models.

🎁 Benefits

Equal opportunity employer.
Reasonable accommodations on request.
Inclusive, collaborative technology team.

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