Data & Analytics Engineer, Domain Enablement
- Discuss this with your agent
- Open in Claude
- Open in ChatGPT
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Role details
Tech stack
Job description
The Senior Data & Analytics Engineer is a hybrid builder role focused on enabling business domains onto the Databricks platform by developing governed Silver and Gold assets, reusable semantic patterns, and domain-ready analytical models. This role sits between pure data engineering and pure analytics engineering: it requires enough technical depth to work comfortably with transformations and lakehouse patterns, and enough business fluency to build trustworthy models that business stakeholders can use and extend.
Initial focus for this role is expected to be G&A and GTM-oriented domains such as Accounting, Program Finance, RevOps, Marketing, HR, and adjacent business functions, while remaining flexible enough to support more complex future domains such as Product or Engineering as the team matures. This role is not a dashboard factory; it is responsible for durable, governed datasets and semantic assets that accelerate domain self-service while maintaining enterprise consistency.
What you’ll do:
- Build and maintain Silver and Gold data models, domain marts, curated datasets, and semantic assets for priority domains onboarding to Databricks.
- Partner directly with business stakeholders to translate domain requirements and KPI definitions into governed, testable, and reusable transformation logic.
- Apply enterprise modeling standards, naming conventions, semantic definitions, and promotion rules, contributing practical improvements back into those standards.
- Create reusable domain patterns and analytical building blocks that allow teams such as FP&A, RevOps, and Marketing to operate more self-service over time.
- Support the design of semantic views and curated layers that can be consumed by BI tools, Databricks SQL, and Genie or related AI/BI experiences.
- Work across domain boundaries when metrics overlap or interact, especially where G&A, GTM, workforce, and product-adjacent concepts intersect.
- Ensure data sensitivity, classification, and approved use are reflected in modeling choices, joins, and semantic exposure, particularly for regulated or restricted datasets.
- Review and refine partner-delivered or domain-contributed data models to ensure they are production-worthy, understandable, and aligned with enterprise definitions.
- Help domain teams grow into more self-service analytics by providing patterns, documentation, examples, and technical guidance rather than permanently centralizing every request.
Requirements
- 5+ years of experience in analytics engineering, BI engineering, data engineering, or a hybrid role spanning modeling and transformation work.
- Strong dimensional modeling and semantic design skills, including facts, dimensions, grain, conformed dimensions, and business-friendly analytical structures.
- Strong SQL skills and comfort working with modern cloud data platforms such as Databricks.
- Ability to translate ambiguous business requirements into precise, auditable, and reusable data models.
- Enough data engineering fluency to work comfortably in Silver-to-Gold transformations, testing, performance tuning, and production deployment contexts.
- Ability to understand the business meaning and usage constraints of the data being modeled, not just the technical transformations involved.
- Strong communication skills and comfort working directly with business stakeholders in domains with evolving definitions and priorities., * Experience in finance, program finance, RevOps, marketing analytics, HR analytics, product analytics, or another cross-functional business domain.
- Experience building modular, tested transformation pipelines on Databricks (SQL/pyspark, Delta Live Tables, or equivalent).
- Experience with semantic layer tooling, governed metrics, or AI/BI consumption layers.
- Experience in regulated or security-sensitive industries.
- Ability and interest to expand from initial G&A/GTM domain focus into more technical domains such as Product or Engineering over time.
Benefits & conditions
Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know., In-Office or Remote United States 160K-240K Annually Senior level 160K-240K Annually Senior level Aerospace * Artificial Intelligence * Machine Learning * Robotics * Software Lead enterprise strategy and operations: develop multi-year strategic plans, build financial models for capital allocation, translate priorities into cross-functional execution with KPIs, and track performance to sustain execution velocity. Top Skills: AechelonAutonomyHivemindV-BatX-Bat Shield AI, In-Office or Remote United States 190K-290K Annually Expert/Leader 190K-290K Annually Expert/Leader Aerospace * Artificial Intelligence * Machine Learning * Robotics * Software Lead multi-year strategic planning and annual operating cycles, evaluate portfolio tradeoffs, build financial models for capital allocation, and translate strategy into cross-functional execution plans with KPIs. Conduct market sizing, competitive analysis, scenario modeling, and track performance through operating cadences to identify bottlenecks and recommend solutions. Top Skills: AechelonHivemindV-BatX-Bat Shield AI, Remote USA 190K-290K Annually Expert/Leader 190K-290K Annually Expert/Leader Aerospace * Artificial Intelligence * Machine Learning * Robotics * Software Lead enterprise systems and data architecture across business domains, define target-state architectures and integration patterns, rationalize shadow IT, guide sensitive-data placement in regulated multi-environment contexts, support major strategic programs, establish architecture governance and review practices, and coach engineering teams to raise architectural maturity. Top Skills: APIsBatch Data MovementDatabricksEvent-Driven ArchitectureOracle ErpSAPSnowflake
What you need to know about the Colorado Tech Scene
With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.
Key Facts About Colorado Tech
- Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
- Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
- Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
- Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute
About the company
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.
Apply for this position
This job is hosted externally. Click below to view the full posting and apply.
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Good distractions
Talks and stories from around this role — technically off-topic, practically not.
Moments
Explore playlistsVideos
See allRelated articles
See all
Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production
Data Engineer Salary UK
Stephan Gillich - Bringing AI Everywhere
Navigating the AI Shift