Senior Data Engineer – Cloud Data Products, Analytic Enablement

Highmark Health

Senior Data Engineer transforming data into actionable intelligence for critical business decisions. Designing scalable data solutions using Google Cloud Platform technologies.

Posted 5/22/2026full-timeRemote • Louisiana, Maryland, North Carolina, Pennsylvania, Washington • 🇺🇸 United StatesSenior💰 $102,700 - $164,600 per yearWebsite

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheBigQueryCloudETLGoogle Cloud PlatformLinuxMongoDBMySQLOraclePostgresPythonSQLUnix

About the role

Key responsibilities & impact

Design, develop, and maintain robust data processes and solutions to ensure the efficient movement and transformation of data across multiple systems
Develop and maintain data models, databases, and data warehouses to support business intelligence and analytics needs
Collaborate with stakeholders across IT, product, analytics, and business teams to gather requirements and provide data solutions that meet organizational needs
Monitor work against production schedule, provide progress updates, and report any issues or technical difficulties to lead developers regularly
Implement and manage data governance practices, ensuring data quality, integrity, and compliance with relevant regulations.
Collaborate on the design and implementation of data security measures, including access controls, encryption, and data masking
Mentor other associate and intermediate data engineers as needed
Perform data analysis and provide insights to support decision-making across various departments
Stay current with industry trends and emerging technologies in data engineering, recommending new tools and best practices as needed

Requirements

What you’ll need

5 years of experience in design and analysis of algorithms, data structures, and design patterns in the building and deploying of scalable, highly available systems
5 years of experience in a data engineering, ETL development, or data management role.
5 years of experience in SQL and experience with database technologies (e.g., MySQL, PostgreSQL, MongoDB).
5 years of experience in data warehousing concepts and experience with data warehouse solutions (e.g., Snowflake, Redshift, BigQuery)
7+ years of experience in designing, developing, and meticulously implementing robust data solutions, encompassing sophisticated structuring and transformation of data from diverse, complex source systems.
7+ years of experience in producing high-quality, efficient, and maintainable data-related code that underpins critical stakeholder applications.
7+ years of experience working across a multitude of technology systems, consistently designing innovative solutions or developing impactful data solutions specifically within the complex healthcare or insurance industry.
7+ years of experience in strategically translating intricate business requirements, design mockups, prototypes, and user stories into precise technical designs and highly impactful, scalable data solutions.
7+ years of experience with both SQL and Python, utilizing these languages for sophisticated data manipulation, advanced analytical insights, and the development of resilient data pipelines.
5+ years of experience leveraging core GCP data services, including BigQuery, DataFlow, Cloud Composer (Managed Airflow), DataProc, and Cloud Run, optimizing their use for cloud-native data architectures.
5+ years of experience with traditional on-premise database systems, including Oracle, Teradata, and DB2, bridging legacy and modern data landscapes.
5+ years of experience operating within Unix/Linux environments, including scripting and system-level data operations.
Holds practical experience with dbt (data build tool) for advanced data transformation and the development of sophisticated analytical data models.
Experienced with cutting-edge data virtualization tools such as Starburst (Trino) or other composable data platforms, enabling unified access to distributed data assets.
Skilled in leveraging advanced data quality engines (e.g., Monte Carlo, Soda) to ensure proactive data observability, integrity, and reliability across the data landscape.
Familiar with sophisticated data catalog systems (e.g., Atlan, Collibra) for comprehensive metadata management, discovery, and robust data governance.
Holds practical experience with Lakehouse technologies and modern open table formats (e.g., Apache Iceberg, Delta Lake), contributing to scalable and flexible data architectures.

Benefits

Comp & perks

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Hard Skills & Tools

data modelingETL developmentSQLPythondata warehousingdata transformationdata analysisdata governancedata qualitydata security

Soft Skills

collaborationmentoringcommunicationproblem-solvingstakeholder engagement