Senior Director, Data & Analytics

Posted today

perkins coieFort Worth (TX)

Data Warehousing SpecialistsComputer Systems Design Services

SENIORITY

Manager

About the role

Overview In this role, you lead the firm’s global data and analytics program, shaping the enterprise data strategy and investment roadmap. You oversee data architecture, governance, analytics, data science, and ML engineering to deliver trusted data products and AI capabilities. You will drive security, reliability, and cost efficiency of data platforms while enabling self-service insights for diverse stakeholders. This is a high-impact, globally distributed leadership role with a strong focus on translating technical priorities into measurable business value. Compensation / Benefitsannual discretionary bonus 401(k) planmedical, dental, and vision insurancepaid time off starting at 20 dayspersonal medical and parental leaveten paid holidays Responsibilities Lead enterprise data and analytics strategy, roadmap, operating model, and investment priorities in partnership with senior leadership Oversee data architecture, engineering, governance, analytics, data science, ML engineering, and enterprise data platforms Own architecture, security, reliability, scalability, performance, and cost efficiency of Databricks and Azure lakehouse Establish enterprise standards for data integration, modeling, quality, governance, metadata, lineage, access, security, and compliance Direct MLOps practices to move models and data products from development to production Enable analytics, AI, and self-service through trusted data products and governed data services Lead build/buy/vendor decisions, platform optimization, and debt reduction Partner with business/tech leaders to translate data/AI opportunities into measurable value Manage budgets, resources, platform costs, risks, and reporting Lead and develop a global, high-performing organization across regions and time zones Foster technical excellence, collaboration, and continuous improvement Key requirements 10+ years in data engineering, analytics, data science, or related tech with enterprise cloud/data solutions 5+ years of senior leadership managing multidisciplinary data/analytics/engineering teams Strong expertise in enterprise data architecture, lakehouse platforms, data integration, modeling, ETL/ELT, and data warehousing Deep experience with Databricks, Microsoft Azure, SQL, Python, and PySpark Working knowledge of ML, MLOps, generative AI, feature stores, model deployment, monitoring, and AI governance Proven track record moving analytics/AI initiatives from prototype to production with business impact Understanding of data quality, governance, security, metadata, lineage, compliance, and data residency Experience managing technology budgets, vendors, platform costs, and cross-functional initiatives Experience leading distributed/global teams across time zones Excellent executive communication, strategic thinking, problem-solving, and leadership Bachelor’s degree in a quantitative discipline; advanced degree preferredexecutive communicationstrategic thinkingproblem-solving Databricks Microsoft AzureSQL

Before you apply

Applying takes about a minute. These four things decide how fast it moves after that.

Your profile is current

It's what we read first. Occupations, seniority and locations matter more than a long history.

Two examples you can talk through

Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.

A number in mind

What you're on now and what would make you move. We negotiate better when we know both.

Your notice period

Employers plan around it, and it's the question that stalls offers most often.

Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.