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The Principal Data Modernization Engineer is a senior technical individual contributor who provides trusted technical leadership across data modernization efforts within CoverMyMeds’ (CMM) Data Technology organization. This role operates across transactional engineering, analytical engineering, platform, and data architecture to ensure modernization initiatives are cohesive, technically sound, and aligned to long-term strategy. This role also partners closely with analytics teams to ensure the data platforms and capabilities being modernized effectively support analytical use cases and evolving business needs.
Job Responsibility:
Act as the Senior Director’s technical delegate for data modernization, providing trusted technical guidance across Data Technology
Guide and shape high-impact modernization decisions that span multiple teams or domains
Provide clarity and direction in complex or ambiguous modernization scenarios, enabling leaders and teams to move forward with confidence
Ensure key technical decisions are clearly articulated, shared, and consistently applied across Data Tech
Proactively identify gaps, inefficiencies, or unclear ownership in data modernization (e.g., ingestion ownership, platform responsibilities, data flow boundaries)
Develop a strong understanding of current-state systems, constraints, and dependencies across teams
Translate ambiguity into clear problem statements, decision options, and technical recommendations
Partner with Engineering and Architecture Directors to align on modernization approaches and technical direction
Bring together the appropriate leaders and senior engineers to explore options, assess trade-offs, and align on paths forward
Foster constructive, outcome-focused discussions that balance technical rigor with practical delivery considerations
Partner with analytics teams to understand analytical usage patterns, performance needs, and downstream considerations that should inform data platform and modernization decisions
Ensure data modernization decisions appropriately support analytics scalability, usability, and long-term analytical flexibility
Guide the application of data modernization patterns and approaches across transactional, analytical, platform, and modeling work, with consideration for downstream analytical consumption and performance needs
Help teams consistently interpret and apply data architecture standards in real-world modernization scenarios
Identify opportunities to simplify, standardize, or improve how modernization patterns are used across Data Tech
Maintain visibility into emerging modernization risks, architectural drift, or areas of growing technical debt
Surface insights and recommendations to leadership early, supporting informed decision-making
Help reduce reliance on informal heroics by promoting clear, repeatable approaches to technical decision-making
Requirements:
Bachelor's degree in Computer Science, Information Systems, or equivalent experience and typically requires 13+ years of relative experience in data engineering, data platforms or large-scale systems
Experience partnering with analytics or reporting teams to ensure data platforms, models and pipelines effectively support analytical workloads and evolving analytical needs
Strong Technical understanding of: Transactional and analytical data systems
Data ingestion, integration, and synchronization patterns
Cloud-based data platforms, specifically Databricks
Data modeling and domain-oriented data design
Demonstrated ability to influence technical direction through credibility, collaboration and clear communication
Experience working effectively in complex, multi-team technical environments
Nice to have:
Experience contributing to or guiding enterprise-scale data modernization initiatives
Strong facilitation and communication skills
able to create clarity in ambiguous situations
Ability to balance long-term architectural thinking with practical delivery realities
Recognized as a trusted technical advisor to senior leaders and peers