Principal Data Engineer/Officer

Principal Data Engineer/Officer

The Principal Data Engineer/Officer serves as a senior strategic advisor to executive leadership, shaping and driving enterprise-wide data strategy across architecture, governance, and organizational design. This role bridges business and technology, leading data maturity assessments, defining forward-looking roadmaps, and clearly communicating complex data concepts to stakeholders ranging from hands-on engineers to C-suite executives. It also plays a key role in client-facing engagements, helping articulate data vision, influence investment decisions, and build confidence in modern data transformation initiatives.

From an execution standpoint, the role is responsible for designing scalable, modern data platforms (lakehouse, Medallion architecture), establishing federated governance models aligned with Data Mesh principles, and guiding tooling and platform decisions across cloud ecosystems. It ensures consistency in semantic layers, BI strategy, and data enablement while driving adoption through operating models, standards, and training frameworks. Ultimately, this position combines deep technical expertise with executive-level communication and leadership to enable organizations to treat data as a strategic asset and operationalize it effectively at scale.

Key Responsibilities

Strategy & Executive Advisory

• Serve as a senior advisor to the CDO or equivalent executive sponsor, providing strategic guidance on modern data architecture, governance models, and enterprise data platform direction
• Develop and communicate a cohesive, actionable data strategy that spans architecture, governance, tooling, and organizational design — tailored to where the organization is today and where it needs to go
• Lead executive-level assessments of current-state data maturity, capability gaps, and investment priorities, producing board- and C-suite-ready roadmaps and recommendations
• Support executive and director-level sales engagements by articulating a compelling data vision, framing strategic opportunity, and building organizational confidence in the proposed direction
• Translate complex architectural and governance concepts into clear, accessible narratives for executives, directors, and team leads — ensuring alignment across all three levels without losing fidelity at any of them

Architecture & Platform Design

• Design and advise on modern data lake and Lakehouse architectures, including Medallion (Bronze / Silver / Gold) and alternative layering strategies appropriate to the organization''s scale and use case complexity
• Define unified semantic layer strategies leveraging open standards (OpenLineage, OpenMetadata, ODCS, and related OSI frameworks) alongside tool-native implementations in platforms such as dbt Semantic Layer, Looker LookML, AtScale, or Cube
• Evaluate and recommend data engineering and ELT strategies including Data Vault 2.0, dimensional modeling, and hybrid approaches — matched to source system complexity, change velocity, and downstream consumption patterns
• Lead platform and tooling architecture decisions across cloud data platforms (Snowflake, Databricks, BigQuery, Redshift, Synapse) with the ability to assess trade-offs across ecosystems without platform bias
• Guide the adoption and scaling of declarative transformation tools including dbt Core and Cloud, Databricks Delta Live Tables (DLT), and emerging alternatives — establishing patterns, standards, and reusable frameworks for engineering teams

Governance & Operating Model

• Design federated data governance models that balance centralized standards with domain-level autonomy, aligned to Data Mesh principles including domain ownership, data as a product, self-serve infrastructure, and federated computational governance
• Define organizational structures for modern data teams, including the roles, responsibilities, and reporting relationships needed to support federated or hybrid operating models at enterprise scale
• Develop governance frameworks covering data ownership, data contracts, data quality standards, access controls, lineage tracking, and metadata management — with a clear path from current state to future state
• Partner with HR, technology leadership, and business unit leads to drive the organizational change management required for data team restructuring, culture shifts, and adoption of new ways of working

Enablement & Reporting Platform Strategy

• Assess and advise on large-scale rollout and rationalization of business intelligence and data enablement platforms, including Tableau, Qlik, Looker, Power BI, ThoughtSpot, and related toolsets
• Define standards for semantic consistency, report governance, self-service analytics enablement, and platform consolidation across heterogeneous BI environments
• Develop adoption strategies, center of excellence models, and training frameworks that accelerate value realization from data enablement investments across large user populations

Required Skills:

• Demonstrated experience functioning as a CDO, VP of Data, or equivalent senior data executive — or in a hands-on advisory role to one — with accountability for strategy, architecture, and organizational outcomes
• Deep, practitioner-level expertise in modern data architecture patterns including Medallion architecture, Data Mesh, Data Vault 2.0, and lakehouse design
• Hands-on experience with declarative and modern ELT tooling, particularly dbt (Core and/or Cloud) and Databricks Delta Live Tables, including establishing team-level patterns and governance around their use
• Proficiency with unified semantic layer design using both open standards (OpenLineage, OpenMetadata, ODCS) and tool-native implementations
• Cross-platform fluency across major cloud data platforms (Snowflake, Databricks, BigQuery, Redshift, Synapse) with the ability to evaluate and recommend without platform bias
• Proven experience designing federated governance models and data team organizational structures, including change management through periods of significant restructuring
• Extensive experience with enterprise BI platform strategy, including large-scale rollout, rationalization, and governance across platforms such as Tableau, Qlik, Looker, and Power BI
• Exceptional ability to communicate across all organizational levels — from hands-on technical leads who need architectural clarity, to directors who need roadmap confidence, to C-suite executives who need strategic vision and financial justification — adjusting depth, framing, and language precisely to each audience without sacrificing accuracy
• Proven track record in executive and director-level client engagement, including the ability to establish credibility quickly, shape strategic narratives, and influence prioritization and investment decisions through clear, compelling communication
• Strong written communication skills for producing strategic assessments, architecture decision records, governance frameworks, and executive-ready presentations

Preferred Skills:

• Experience leading or advising on data strategy in large enterprise or regulated industry environments (telecom, financial services, healthcare)
• Familiarity with emerging semantic and interoperability standards including ODCS (Open Data Contract Standard) and Apache Iceberg / Delta Lake / Hudi at the storage and catalog layer
• Exposure to AI and ML platform integration within the modern data stack, including feature stores, model registries, and the intersection of analytics engineering with ML workflows
• Experience standing up or advising on Data Products as a formal organizational and architectural construct, including defining product ownership, SLAs, and discoverability standards
• Background in enterprise metadata management and data catalog tooling (Alation, Collibra, Atlan, DataHub)
• Familiarity with FinOps practices as applied to data platform cost management and optimization
• Experience supporting pre-sales, proposal development, or thought leadership content as a senior practitioner — contributing to client acquisition through credibility and vision rather than traditional sales motion
• Published work, conference participation, or recognized community presence in the modern data stack ecosystem