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Strong Tier-1 employer but senior leadership, specialized data focus and non-metro location moderate applicant competition.
Data engineering skills broadly transferable, though healthcare domain knowledge slightly increases domain specificity.
High due to explicit 15–20 years requirement and multiple mandatory data, cloud, and DevOps technologies.
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Lead and manage a blended team of analysts and technical practitioners to build scalable, trusted data assets supporting data warehouses, analytics, and process modernization.
Design the data engineering roadmap and architectural standards while ensuring quality, governance, and partnering with technology teams to deploy enterprise-grade production pipelines.
Engineer scalable cloud-based data solutions using AWS services, Databricks, Teradata Vantage, and CI/CD frameworks, emphasizing automation and minimizing manual workflows.
15 to 20 years of experience in application program development or equivalent education and work experience.
Bachelor’s degree in Engineering, Computer Science, or related discipline.
Extensive hands-on experience with AWS services including Lambda, Step Functions, CloudTrail, CloudWatch, SNS, SQS, S3, VPC, EC2, RDS, IAM.
Proficient in Python, Databricks, SQL, Unix, SPARK, and real-time analytics frameworks; experience with SDLC processes and building web services (HTTP API/RPC).
Senior-level leader experienced managing cross-functional data engineering and analytics teams in agile environments.
Strong expertise in AWS cloud-native data engineering with ability to define architecture and governance for enterprise-scale pipelines.
Proven ability to deliver automated, maintainable, and scalable data solutions aligning with strategic business goals and operational excellence.