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Generalist data engineer title with broad cloud and ETL requirements creates moderate competition.
Core SQL, ETL and Python data engineering skills transfer easily across industries.
Multiple mandatory cloud, ETL, SQL technologies and explicit years requirement enforce strict technical filters.
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Build, optimize, and manage scalable data pipelines and ingestion workflows from diverse data sources supporting analytics and reporting.
Develop and optimize complex SQL queries, stored procedures, and data models to enable high-quality data products and business intelligence.
Collaborate with stakeholders to translate business requirements into automated, governed, and performant data solutions, contributing to design, development, and technical leadership within the data team.
Bachelor's degree in Computer Science, Information Technology, or Engineering.
4-10+ years of hands-on experience in SQL development, ETL, and BI/reporting.
Proficiency in T-SQL or PL-SQL with advanced query writing and performance tuning.
Experience with ETL/ELT tools (e.g., SSIS, Azure Data Factory, AWS Glue) and cloud data services on Azure and AWS (e.g., Azure Synapse, ADLS, Lambda, S3).
Experienced in designing and maintaining data models (star/snowflake schemas) and supporting end-to-end data product lifecycle.
Strong programming skills in Python for data engineering and automation, with exposure to data governance and compliance standards.
Capable of collaborating cross-functionally with Product Managers and business stakeholders to deliver analytics-ready, governed datasets aligned with business objectives.