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Senior, specialized data engineering role at mid-tier insurer reduces qualified applicant density.
Core data engineering skills transfer well, though insurance analytics and specific tools require domain familiarity.
Senior data engineering title, required cloud, ELT, and tooling experience makes filtering strict.
Own end-to-end delivery of small to medium scale data pipelines and products using multiple platforms and technologies, including ELT solutions.
Implement and maintain data engineering best practices including source code management, branching, issue tracking, and access controls for data products.
Research, evaluate, and apply big data methodologies and cloud/hybrid hosting solutions (AWS, Hadoop/EMR, Spark, Kafka, Snowflake, Talend) aligned with Enterprise DevOps practices.
Demonstrated data engineering experience with programming, SDLC best practices, and distributed systems.
Experience developing and operating production workloads on cloud infrastructure, preferably AWS.
Strong verbal and written communication skills with the ability to work cross-functionally and translate between business and technical teams.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in delivering data pipelines and data products in an agile and lean environment, familiar with Scaled Agile principles.
Ability to operate across technical stacks including big data tools, cloud platforms, and DevOps toolchains with a transformation mindset.
Effective collaborator capable of influencing leadership and cross-functional teams to mature practices in code quality, automated testing, and environment management.