Lead Data Engineer – Cloud Data Products & Analytic Enablement

Highmark Health is seeking a Lead Data Engineer to transform diverse data sources into actionable intelligence for business decisions and application ecosystems. The role designs, builds, and optimizes scalable cloud data pipelines and develops curated datasets, analytical assets, data models, and governed data products using Google Cloud Platform technologies, SQL, and Python.

Responsibilities:

• Lead the design, develop, and maintain robust data processes and solutions to ensure the efficient movement and transformation of data across multiple systems
• Oversee development 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
• Mentor other associate, intermediate, and senior data engineers as needed
• Collaborate with other Data Leaders to ensure consistency of data solutions across systems and platforms
• Monitor work against the 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
• Stay current with industry trends and emerging technologies in data engineering, recommending new tools and best practices as needed
• Other duties as assigned or requested

Requirements:

• CANDIDATE MUST BE US Citizen (due to contractual/access requirements)
• • 7 years of experience in design and analysis of algorithms, data structures, and design patterns in the building and deploying of scalable, highly available systems
• • 7 years of experience in a data engineering, ETL development, or data management role
• • 7 years of experience in SQL and experience with database technologies (e.g., MySQL, PostgreSQL, MongoDB)
• • 7 years of experience in with data warehouse solutions and concepts (e.g., Snowflake, Redshift, BigQuery)
• • Demonstrated ability to achieve stretch goals in a highly innovative and fast-paced environment
• • Adaptability Advanced ability to take on diverse tasks and projects, adapting to the evolving needs of the organization
• • Analytical Thinking Advanced analytical skills with a focus on detail and accuracy
• • Interest and ability to learn other data development technologies/languages as needed
• • Technical Proficiency Comfortable with a range of data tools and technologies, with a willingness to learn new skills as needed
• • Advanced track record in designing and implementing large-scale data sources
• • Advanced sense of ownership, urgency, and drive
• • Demonstrated passion for user experience and improving usability
• • Team Collaboration A team player who can work effectively in cross-functional environments
• • Experience and willingness to mentor junior data engineers and help develop their skills and leadership
• • Bachelor's degree in Computer Science, Information Systems, Data Science, Computer Engineering or related field
• 0% - 25%
• Lifting up to 10 pounds
• Lifting 10 to 25 pounds
• Lifting 25 to 50 pounds
• • 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
• • Possesses proven, hands-on experience with dbt (data build tool) for advanced data transformation and the development of sophisticated analytical data models
• • Experienced with 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
• • Master's degree in Computer Science, Information Systems, Data Science, Computer Engineering or related field