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Data Platform Engineering Director Jobs (NOW HIRING)

Northern Base

Data Platform Engineering Lead

Irvine, CA · On-site

Data Platform Engineering Lead Irvine, CA FUlltime Data Platform Engineering Lead Must Have Technical/Functional Skills Data Bricks , EBT ,Airflow , Asset Management exp Roles & Responsibilities We ...

The Hartford

AVP, Data Platform Engineering

Hartford, CT · On-site

$177K - $266K/yr

As the AVP, Data Platform Engineering, you will provide strategic and technical leadership for enterprise data platforms, analytics capabilities, data integration services, AI-enabled data solutions ...

Judge Group, Inc.

Data Platform Engineering Lead

Tustin, CA · On-site

$160K - $170K/yr

Data Platform Engineering Lead Irvine, CA Fulltime Must Have Technical/Functional Skills Data Bricks , EBT ,Airflow , Asset Management exp Roles & Responsibilities We are seeking a highly skilled EDO ...

The Hartford

AVP, Data Platform Engineering

Hartford, CT · On-site

$115K - $138K/yr

As the AVP, Data Platform Engineering, you will provide strategic and technical leadership for enterprise data platforms, analytics capabilities, data integration services, AI-enabled data solutions ...

The Hartford

AVP, Data Platform Engineering

Charlotte, NC · On-site

$177K - $266K/yr

As the AVP, Data Platform Engineering, you will provide strategic and technical leadership for enterprise data platforms, analytics capabilities, data integration services, AI-enabled data solutions ...

The Hartford

AVP, Data Platform Engineering

Charlotte, NC · On-site

$111K - $134K/yr

As the AVP, Data Platform Engineering, you will provide strategic and technical leadership for enterprise data platforms, analytics capabilities, data integration services, AI-enabled data solutions ...

Mosaic Health

Director, Data Engineering & Platform

Summary The Director, Data Engineering & Platform provides M4-level organizational leadership for the execution of the enterprise data engineering and platform vision and strategy established by the ...

Hasbro

Manager, Data Platform Engineering

Boston, MA

This team builds and operates the shared platform that data engineers, analytics engineers, data ... Direct experience with Databricks and/or Snowflake, and the judgment to evaluate platforms against ...

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Data Platform Engineering Director information

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$73K

$194.7K

$254K

How much do data platform engineering director jobs pay per year?

As of Sep 9, 2026, the average yearly pay for data platform engineering director in the United States is $194,709.00, according to ZipRecruiter salary data. Most workers in this role earn between $141,500.00 and $253,000.00 per year, depending on experience, location, and employer.

What is the difference between Data Platform Engineering Director vs Data Engineering Manager?

AspectData Platform Engineering DirectorData Engineering Manager
ResponsibilitiesOversees the design, development, and strategy of data platforms, ensuring scalability and performanceManages data engineering teams, oversees project execution, and ensures data pipelines meet business needs
Required SkillsStrong leadership, architecture expertise, cloud platforms, and data systems knowledgeTechnical data engineering skills, team management, project coordination
Work EnvironmentStrategic, cross-departmental, often executive-level collaborationOperational, team-focused, project-driven
Common UsageUsed in large organizations for high-level data infrastructure strategyUsed in organizations of all sizes for managing data engineering teams

The Data Platform Engineering Director focuses on strategic oversight and architecture of data platforms, while the Data Engineering Manager handles day-to-day team management and project execution. Both roles require technical expertise, but differ in scope and level of responsibility.

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Infographic showing various Data Platform Engineering Director job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 83% Full Time, 12% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $194,709 per year, or $93.6 per hour.

Director, Data Platform Engineering

Milford, MA • On-site

Waters Corporation
Biotechnology Research and Development • 5 - 10K employees
Learn more about Waters Corporationexternal

$277K/yr

Other

Posted 16 days ago

Job description

Overview
Waters runs on data. The Enterprise Data Platform is how that data gets governed, trusted, and delivered to the entire business. The Director, Data Platform Engineering owns this platform end to end: the infrastructure, the governance model, the engineering standards, and the architecture that connects every system in our data estate to every team that depends on it. Data engineering, analytics, data science, commercial, finance, and operations teams across 100-plus countries rely on what you build. This is a hands-on role. You will architect, build, and govern alongside your team, not above them, while leading a direct platform engineering team and a matrixed Global Capability Center (GCC) team with a delivery model that keeps both aligned and the platform moving forward. If you want a role where the platform you build has company-wide reach and a direct line to Waters' Data and AI strategy, this is it.
You will report to the Senior Director, Enterprise IT Data and Analytics and serve as the technical authority for Waters' Enterprise Data Platform, accountable for platform reliability, governance, cost efficiency, and engineering excellence across a global, distributed team.
Responsibilities
Key Responsibilities
Hands-On Platform Architecture & Engineering
  • Design, build, and own the end-to-end architecture of Waters' Enterprise Data Platform: Databricks Lakehouse, Power BI semantic layer, and SAP integration touchpoints.
  • Personally lead Infrastructure as Code implementation in Terraform: workspaces, Unity Catalog objects, compute policies, access bindings, and CI/CD pipelines. You write the modules, not just approve them.
  • Architect and enforce Unity Catalog governance: fine-grained permissions, data classification, lineage, row and column-level security, and audit controls for a regulated life-sciences environment.
  • Drive Delta Lake architecture decisions, cluster optimization, job orchestration patterns, and platform observability across development, staging, and production environments.
  • Partner closely with data engineering, analytics, and data science teams to ensure compute environments are stable, performant, and right-sized for their workloads. You are their platform partner, not their ticket queue.

Power BI & Analytics Platform Engineering
  • Build and govern a high-performance Power BI enterprise environment: semantic models, deployment pipelines, workspace governance, RLS, and certified dataset standards.
  • Serve as the technical bridge between the Databricks Lakehouse and Power BI consumption layer; ensure models are reliable, performant, and self-service ready for business consumers.
  • Define and enforce BI engineering standards across the analytics team, covering DAX best practices, incremental refresh, composite models, and dataflow architecture.

AI Platform Enablement & Data and AI Strategy
  • Evaluate, implement, and support AI and ML platform capabilities aligned with Waters' Data and AI strategy, including model lifecycle management, feature engineering, model registry, vector search, and AI gateway infrastructure on Databricks.
  • Ensure the end-to-end data estate is AI-ready: catalog completeness, data quality standards, lineage coverage, and access controls that support reliable model training, evaluation, and inference pipelines at scale.
  • Govern AI workloads on the platform: data access controls for training pipelines, model artifact storage, inference endpoint security, and audit trails that meet Waters' life-sciences compliance requirements.
  • Partner with data science, analytics, and business stakeholders to translate AI use case requirements into platform architecture decisions, building the infrastructure that enables AI outcomes without owning the models themselves.
  • Maintain current knowledge of AI platform capabilities across the stack (Databricks AI, Microsoft Copilot and Fabric AI, MLflow, and emerging open-source frameworks); provide evidence-based recommendations on adoption timing, cost, and risk.

Platform Operations: Establishing the Practice
  • Build and formalize a Platform Operations discipline from the ground up: define runbooks, operational playbooks, change management standards, and escalation protocols for the full data estate.
  • Establish SLAs and SLOs for platform reliability: Databricks workspace uptime, job success rates, Power BI refresh SLAs, and data pipeline latency targets.
  • Implement platform health monitoring and observability: dashboards, alerting, and incident response workflows that provide proactive visibility across the environment.
  • Own the on-call and incident management model for platform engineering: triage, root cause analysis, post-mortems, and continuous improvement loops.
  • Define and enforce a change management process for platform configuration, infrastructure updates, and governance policy changes across the direct and GCC teams.

Direct Team & GCC Leadership
  • Lead and develop a direct team of platform engineers; conduct architecture reviews, set sprint priorities, and model disciplined engineering practices.
  • Own the delivery model for the matrixed GCC engineering team: define work packages, quality standards, SLAs, escalation paths, and onboarding protocols that make the GCC a genuine force multiplier.
  • Establish clear communication rhythms across time zones: async documentation standards, structured handoffs, and review gates that preserve quality without creating bottlenecks.
  • Grow individual engineers: define career paths, close skill gaps, and maintain team capability aligned to the platform roadmap.

Data Governance, Security & Compliance
  • Own platform-level data governance: Unity Catalog permissions, data classification, lineage, and audit controls aligned with Waters' life-sciences compliance posture. GxP and 21 CFR Part 11 awareness valued.
  • Enforce least-privilege access models, service principal governance, and cross-domain data sharing protocols.
  • Champion data quality, observability, and incident response practices; define SLAs and SLOs for platform reliability.

Roadmap, FinOps & Stakeholder Partnership
  • Partner with the Senior Director to translate business priorities into platform roadmap milestones with clear ownership and delivery dates.
  • Own total cost of ownership for the data platform: Databricks compute governance, Power BI Premium capacity, FinOps discipline, and cloud spend accountability.
  • Engage Databricks, Microsoft (Azure/Power BI), and SAP vendor partners proactively to surface and leverage platform capabilities.
  • Represent platform engineering in architecture reviews, enterprise risk discussions, and IT steering committees.

Qualifications
Required Qualifications
  • 10-plus years of hands-on experience in data platform engineering or data architecture; 5-plus years at a senior or lead level with direct team responsibility.
  • Deep, current expertise in Databricks: Unity Catalog, workspace administration, compute governance, Delta Lake, and Lakehouse architecture. You can demonstrate this in a whiteboard or code review.
  • Proven Power BI experience at enterprise scale: semantic models (tabular/DAX), deployment pipelines, workspace governance, and enterprise RLS.
  • Strong Infrastructure as Code proficiency in Terraform for cloud data infrastructure, including CI/CD integration, state management, and module design best practices.
  • Demonstrated experience leading both direct and GCC or distributed engineering teams; ability to build delivery models that create accountability across time zones.
  • Solid foundation in cloud platforms (Azure or AWS), IAM, networking, and enterprise security patterns.
  • Strong communicator, fluent in engineering depth and business context and credible with senior leadership, HR, and external candidates.
  • Working knowledge of AI and ML platform patterns and MLOps: model lifecycle management, training pipeline infrastructure, model serving, and monitoring at enterprise scale.

Preferred Qualifications
  • Experience with SAP BPC (Business Planning & Consolidation) or SAP SAC (Analytics Cloud) in an enterprise environment.
  • Background in a regulated industry such as life sciences, pharma, or medical devices, with familiarity with GxP or 21 CFR Part 11 data integrity requirements.
  • Databricks certifications (Data Engineer Professional, Platform Administrator, or Architect).
  • Experience with GitHub Actions CI/CD pipelines for data infrastructure.
  • FinOps experience: cost tagging, cluster right-sizing, compute policy design, and cloud spend forecasting.
  • Hands-on experience with GenAI or LLM infrastructure: RAG architectures, vector databases, embedding pipelines, or AI and LLM gateway configuration on an enterprise data platform.

Company Description
Waters Corporation (NYSE:WAT) is a global leader in life sciences and diagnostics, dedicated to accelerating the benefits of pioneering science through analytical technologies, informatics, and service. With a focus on regulated, high-volume testing environments, our innovative portfolio harnesses deep scientific expertise across chemistry, physics, and biology. We collaborate with customers around the world to advance the release of effective, high-quality medicines, ensure the safety of food and water, and drive better patient outcomes by detecting diseases earlier, managing routine infections, and combating antibiotic resistance. Through a shared culture of relentless innovation, our passionate team of ~16,000 colleagues turn scientific challenges into breakthroughs that improve lives worldwide.
Diversity and inclusion are fundamental to our core values at Waters Corporation. It benefits our employees, our products, our customers and our community. Waters complies with all applicable federal, state, and local laws. Qualified applicants are considered without regard to sex, race, color, ancestry, national origin, citizenship status, religion, age, marital status (including civil unions), military service, veteran status, pregnancy (including childbirth and related medical conditions), genetic information, sexual orientation, gender identity, legally recognized disability, domestic violence victim status, or any other characteristic protected by law. Waters is proud to be an equal opportunity workplace and is an affirmative action employer. All hiring decisions are based solely on qualifications, merit, and business needs at the time.

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