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Generalist data engineer title with broad cloud and ETL stack increases applicant competition.
Core data engineering skills (SQL, Python, ETL) are highly transferable across industries.
Explicit 10+ years and many mandatory cloud, SQL, ETL, and Python requirements enforce strict filtering.
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Build, optimize, and manage scalable data ingestion workflows and pipelines from multiple structured and unstructured sources.
Develop and optimize SQL queries, stored procedures, and data models to support high-volume analytics, reporting, and data products.
Collaborate with business stakeholders to translate requirements into automated, governed, and high-quality data solutions enabling data-driven decision-making.
Bachelor's degree in Computer Science, Information Technology, or Engineering.
4 to 10+ years of hands-on experience in SQL development, ETL, and BI/reporting.
Strong proficiency with SQL (T-SQL/PL-SQL) and advanced query performance tuning.
Hands-on experience with ETL/ELT tools (e.g., SSIS, Azure Data Factory, Fivetran, AWS Glue) and cloud data services on Azure and AWS platforms.
Experienced in end-to-end data engineering working with cloud platforms like Azure and AWS and familiar with data warehousing concepts and dimensional modeling.
Capable of designing, developing, and maintaining scalable, automated data pipelines and data products with attention to data governance and security.
Skilled at collaborating closely with business stakeholders and product managers to deliver actionable data insights and continuous improvement in data workflows.