Senior Analytic Data Engineer – Cloud Data Products & Analytic Enablement

JOB SUMMARY

As a Senior Analytic Data Engineer – Cloud Data Products & Analytic Enablement, you will be instrumental in transforming diverse data sources into actionable intelligence, empowering critical business decisions across our organization and within our application ecosystem. This pivotal role demands a strong foundation in data engineering principles, combined with a keen focus on analytical engineering to unlock the full potential of our data assets.

You will leverage deep expertise in Google Cloud Platform (GCP) technologies, including Managed Airflow (Cloud Composer), Big Query, Cloud Run Functions, Data Flow, Data Proc, and Data Plex, to design, build, and optimize scalable data pipelines. Your work will encompass the entire data lifecycle from ingestion and processing to modeling and orchestration, ensuring the highest standards of data quality, performance, and governance.

A core aspect of this role involves translating complex engineered data into readily consumable, business-ready insights by developing curated datasets and robust analytical assets. Success in this position requires exceptional proficiency in SQL and Python, coupled with the ability to strategically partner with diverse stakeholders, translating intricate business requirements into impactful, scalable data products.

• Work closely with IT, architect and engineer solutions that provide views for the Analytic Data Warehouse.
• Assist with the design, building out the solution, and provide upkeep for the solution.
• Assemble, test, process, and maintain the Analytic Discovery Platform for analytics organizations.
• Maintain pipelines with key analytic platforms throughout the organization.
• Work with alternative analytic data systems to incorporate them into the operational data flow for Analytics Teams, including products purchased by the organization that must be ingested or modeled/derived data maintained by analytic teams.
• Lead functional efforts for assigned projects with limited supervision.
• Guide and educate intermediate contributors within this team.
• Meet individually with customers for specific projects and attend with intermediates for support.
• Ensure compliance with HIPAA and other data security guidelines.
• Other duties as assigned.

Bachelor's Degree in Computer Systems Analysis, Data Processing, Healthcare Informatics, Management Information Systems, or related field. (Preferred Master’s Degree in Management Information Systems.)

• 3 - 5 years of Data Analytics experience (required).
• 7+ years designing, developing, and implementing robust data solutions, including sophisticated data structuring and transformation from diverse, complex source systems.
• 7+ years producing high-quality, efficient, and maintainable data-related code underpinning critical stakeholder applications.
• 7+ years working across a multitude of technology systems, consistently designing innovative solutions within the complex healthcare or insurance industry.
• 7+ years strategically translating intricate business requirements, mockups, prototypes, and user stories into precise technical designs and scalable data solutions.
• 7+ years of experience with SQL and Python for advanced data manipulation, analytical insights, and resilient data pipelines.
• 5+ years leveraging core GCP data services, including Big Query, Data Flow, Cloud Composer, Data Proc, and Cloud Run, optimizing them for cloud-native architectures.
• 5+ years of experience with traditional on-premise database systems such as Oracle, Teradata, and DB2.
• 5+ years operating within Unix/Linux environments, including scripting and system-level data operations.
• Proven hands‑on experience with dbt for advanced transformation and analytical data models.
• Experience with data virtualization tools such as Starburst (Trino) or other composable platforms.
• Skilled using data quality engines (e.g., Monte Carlo, Soda) for proactive observability, integrity, and reliability.
• Familiar with data catalog systems (e.g., Atlan, Collibra) for comprehensive metadata management and governance.
• Experience with lakehouse technologies and modern open table formats (Apache Iceberg, Delta Lake).

Google Professional Cloud Data Engineer (preferred).

• Microsoft Office
• SAS Language

0% - 25%.

• Position type:
  Office‑Based
• Occasional travel: from office to various work sites
• Never physical work site required
• Lifting: up to 10 pounds occasionally; 10‑25 pounds rarely; 25‑50 pounds never

Minimum: $94,200.00 | Maximum: $.

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