Base pay is influenced by several factors including a candidate’s qualifications, relevant experience, and anticipated contributions to meet the needs of the business, along with internal pay equity and external market driven rates. The salary range displayed has not been adjusted for geographical location. This range has been created in good faith based on information known to Capital Blue Cross at the time of posting and may be modified in the future. Capital Blue Cross offers a comprehensive benefits packaging including Medical, Dental & Vision coverage, a Retirement Plan, generous time off including Paid Time Off, Holidays, and Volunteer time off, an Incentive Plan, Tuition Reimbursement, and more. 

The Data Engineer II designs and maintains scalable cloud-based data pipelines and models to support reliable data products. This role involves hands-on ELT development, data quality assurance using the Audit, Balance, Control (ABC) framework, and consultative collaboration with analysts and stakeholders. It requires strong SQL and Python skills, experience with cloud data tools and modeling techniques, and a proactive, agile approach to data engineering and governance.

• Build, refactor, and maintain pipeline components of data products for a cloud environment.
• Own the ingestion, storage, cleansing, profiling, transformation, and presentation of data products.
• Analyze large and complex datasets for quality, accuracy, anomalies, and performance.
• Own pre-UAT testing for every change using the standard ABC framework.
• Consultatively interface with analysts and stakeholders on new data requests, enhancements, recommendations, quality, and awareness items.
• Assess project-specific integration restrictions/options and recommend load strategy, storage targets, data access layer model, and solution architecture.
• Participate in modeling star-schema data marts, denormalized performant layers, presentation layers, and Data Vault (or other immutable storage).
• Organize source code with versioning framework.
• Create and maintain project-specific reference architecture diagrams and engineering-oriented documentation.
• Triage emergent data concerns and coordinate with stakeholders through resolution.

Skills:

• Demonstrated ability to program advanced SQL and Python.
• Demonstrated ability to write and maintain scripts using Bash (Unix shell), PowerShell, or DOS batch scripting.
• Demonstrated ability to use ELT applications such as WhereScape or IDMC.
• Demonstrated ability to present at team-wide code reviews.
• Demonstrated ability to proactively analyze and resolve data issues in an agile, collaborative environment.

Knowledge:

• Knowledge of data ingestion using unstructured, semi-structured, and structured data.
• Knowledge of data quality concepts and the ABC framework.
• Familiar with source code versioning tools such as Git.
• Comprehensive understanding of both Star Schema modeling and Normalized Relational modeling. Understanding of Data Vault 2.1 is a plus.
• Foundational knowledge of data preparation needs for Large Language Models.
• Familiar with metadata capture, row access policies, data masking policies, and data governance principles.

Experience:

• 3+ years in database technologies and data engineering experience
• 3+ years of modeling, building, and testing data products experience
• 2+ years in cloud data infrastructure with a SaaS delivery model. Azure and Snowflake experience are a plus.
• Healthcare experience is preferred

Education and Certifications:

• Bachelor’s Degree in Computer Science, Software Engineering, Healthcare Informatics or related studies; or 7 years of relevant experience in lieu of degree.

Work Environment:

• Ability to provide off-hours assistance to support critical time sensitive data products. Ability to handle multiple assignments concurrently. Ability to adapt to changing priorities of multiple customers. Ability to work independently and/or as a member of a project team.