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Remote, popular data-engineer role with metro location and broad skillset increases applicant competition.
Data engineering skills like ETL, SQL, and Python are widely transferable across industries.
Explicit 1–3 year requirement plus mandatory Python, SQL, ETL, and Airflow skills raise filtering strictness.
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Design, build, and maintain scalable data pipelines and workflows ensuring high data quality.
Develop and optimize ETL/ELT processes and reusable data processing scripts for validation, enrichment, and formatting.
Collaborate with cross-functional teams for data workflow management, documentation, and codebase standardization.
1-3 years of experience in data engineering or related roles.
Strong experience in Python including Pandas, SQLAlchemy, and Airflow operators.
Intermediate to advanced proficiency in SQL and hands-on experience with ETL/ELT processes.
Familiarity with orchestration tools like Airflow or Prefect and experience with data warehouses such as PostgreSQL, Redshift, or BigQuery.
Experienced in managing and optimizing end-to-end data workflows from ingestion to transformation with automation of recurring tasks.
Capable of building data models, materialized views and implementing data quality and integrity validation frameworks.
Comfortable working with version control (Git) and supportive technologies like Docker, with good communication skills for stakeholder collaboration.