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Mid-level data engineering role with common cloud, ETL, and BI skills attracts moderate competition.
Core data engineering skills are transferable, though life-sciences domain familiarity is beneficial.
Explicit 5–8 years plus multiple mandatory cloud, ETL, and BI technology requirements increase strictness.
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Develop, design, and manage a cloud-hosted data warehouse ensuring efficient operations and data integrity.
Establish data analysis capabilities using PowerBI and implement integration platform strategies for data extraction governance.
Lead data engineering initiatives, including designing, optimizing data pipelines, and providing mentorship to junior team members.
Bachelor’s degree in computer science or information systems.
5-8 years of hands-on experience in end-to-end data engineering.
At least 5 years experience with cloud technologies (Snowflake, Microsoft Azure), ETL/orchestration tools (Workato, Azure Data Factory, Talend), and BI tools (Power BI, Tableau).
Proficiency in SQL, data modeling, Git, DevOps, CI/CD pipelines, and working with large data sets (terabytes+).
Experienced in managing large-scale data ecosystems focused on data reliability and availability.
Skilled communicator able to translate complex technical data concepts to non-technical stakeholders and guide data quality standards.
Operates effectively in fast-paced, cross-functional environments requiring flexibility and problem-solving under changing priorities.