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A
Senior Director, Data & Analytics
Ashurst Perkins Coie. Lead the firm’s enterprise data and analytics strategy, roadmap, operating model, and investment priorities .
Posted 9/18/2026full-timeSeattle • Arizona • United StatesSenior💰 $190,310 - $379,380 per yearWebsite
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive expertise in enterprise data architecture, analytics, and machine learning engineering, with a strong focus on leading multidisciplinary teams and driving measurable business impact through data-driven strategies. Proficient in managing technology budgets, vendor relationships, and ensuring compliance with data governance and security standards.
Highest-signal resume keywords
Enterprise Data ArchitectureDatabricksMicrosoft AzureMachine Learning EngineeringData Governance
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringAnalyticsData ScienceETL/ELTDimensional ModelingSQLPythonPySparkData WarehousingMLOps
Soft Skills
Executive CommunicationStrategic ThinkingProblem-SolvingLeadership
Tools & Technologies
Unity CatalogMicrosoft FabricPower BIDenodoEmerging AI Platforms
Industry Keywords
Professional ServicesClient ConfidentialityData ResidencyRegulatory Requirements
Tech Stack
Tools & technologiesAzureCloudETLPySparkPythonSQLUnity
About the role
Key responsibilities & impact- Lead the firm’s enterprise data and analytics strategy, roadmap, operating model, and investment priorities
- Oversee data architecture, engineering, governance, analytics, data science, machine learning engineering, and enterprise data platforms
- Own the architecture, security, reliability, scalability, performance, and cost efficiency of the Databricks and Microsoft Azure lakehouse environment
- Establish enterprise standards for data integration, modeling, quality, governance, metadata, lineage, access, security, and compliance
- Direct machine learning engineering and MLOps practices, ensuring models and data products move reliably from development to production
- Enable analytics, AI, and self-service capabilities through trusted data products, semantic models, and governed data services
- Lead build, buy, and partner decisions, including vendor management, technology investments, platform optimization, and technical debt reduction
- Partner with business and technology leaders to identify opportunities for data, analytics, and AI and translate technical priorities into measurable business value
- Manage budgets, resources, platform consumption, risks, and executive reporting across the data organization
- Lead and develop a high-performing global organization across multiple regions and time zones
Requirements
What you’ll need- 10-plus years of progressive experience in data engineering, analytics, data science, or related technology disciplines, including enterprise cloud and data solutions
- 5-plus years of senior leadership experience managing multidisciplinary data, analytics, engineering, or technology teams, including people managers
- Strong expertise in enterprise data architecture, lakehouse platforms, data integration, dimensional and semantic modeling, ETL/ELT, and data warehousing
- Deep experience with Databricks, Microsoft Azure, SQL, Python, and PySpark
- Working knowledge of machine learning, MLOps, generative AI, feature stores, model deployment, monitoring, and AI governance
- Demonstrated experience taking analytics, data science, or AI initiatives from prototype through production and measurable business impact
- Strong understanding of data quality, governance, security, metadata, lineage, compliance, and data residency requirements
- Experience managing technology budgets, vendors, platform costs, and cross-functional initiatives
- Experience leading distributed or global teams across multiple regions and time zones
- Excellent executive communication, strategic thinking, problem-solving, and leadership skills
- Bachelor’s degree in computer science, engineering, statistics, or a related quantitative discipline; equivalent experience may be considered
- Experience with Elite 3E and related professional services or practice management data structures
- Experience with Databricks, Unity Catalog, Microsoft Fabric, Power BI, Denodo, and emerging AI or agentic AI platforms
- Experience in a law firm or professional services environment, including client confidentiality, matter-level data, data residency, and regulatory requirements
Benefits
Comp & perks- Annual discretionary bonus
- 401(k) plan
- Medical insurance
- Dental insurance
- Vision insurance
- Accrued paid time off plan starting at 20 days annually
- Personal medical leave
- Parental leave
- Up to ten paid holidays
- Family care benefits