Data Platform Lead
Job Summary
As a technology leader that is rapidly on the move HARMAN is filled with people who are focused on making life better. Innovation inclusivity and teamwork are a part of our DNA. When you add that to the challenges we take on and solve together youll discover that at HARMAN you can grow make a difference and be proud of the work you do every day.
Introduction: A Career at HARMAN Automotive
Were a global multi-disciplinary team thats putting the innovative power of technology to work and transforming tomorrow. At HARMAN Automotive we give you the keys to fast-track your career.
- Engineer audio systems and integrated technology platforms that augment the driving experience
- Combine ingenuity in-depth research and a spirit of collaboration with design and engineering excellence
- Advance in-vehicle infotainment safety efficiency and enjoyment
About the Role
We are looking for a Data Platform Lead to own the technical direction architecture engineering capability operation and continuous evolution of HARMAN Automotives Enterprise Data Platform.
Built primarily on Microsoft Azure and Azure Databricks the platform enables enterprise data engineering governed data products data sharing analytics and AI at scale. The Data Platform Lead is accountable for the technical architecture and engineering standards of the platform and for ensuring it is secure reliable scalable cost-effective and easy for domain teams to adopt.
The role leads a multidisciplinary technical team spanning Platform Engineering Data Engineering Data Product Enablement and Site Reliability Engineering. The Platform Lead sets technical direction develops engineering talent balances platform engineering and reliability priorities and ensures the team can support data product teams without becoming the permanent development organization for every business domain.
The Data Platform Lead works closely with the Data Platform Portfolio Manager Enterprise Architecture Cybersecurity Analytics MDM and Data Quality business domains and other technology teams. Enterprise Architecture provides enterprise standards architecture review and alignment while the Data Platform Lead retains accountability for the architecture and technical evolution of the Enterprise Data Platform.
An external implementation partner will initially build significant portions of the platform. The Data Platform Lead will work alongside the partner retain HARMANs technical decision rights ensure continuous knowledge transfer and establish the internal capabilities required to operate and evolve the platform as external implementation capacity decreases.
What You Will Do
- Own the technical architecture engineering direction and evolution of the Enterprise Data Platform with Azure Databricks as the strategic enterprise data and AI platform.
- Define and maintain platform architecture standards technical patterns architecture decisions and guardrails across Databricks Azure services identity networking security storage governance automation and operations.
- Own the technical platform roadmap and lifecycle including platform capabilities architecture evolution technical debt reliability improvements automation and engineering investments.
- Partner with the Data Platform Portfolio Manager on demand dependencies sequencing and capacity while retaining ownership of the platform capability and technical roadmap.
- Manage the platform as an enterprise product and service with defined capabilities service expectations measurable outcomes adoption goals and a strong focus on developer and user experience.
- Lead a multidisciplinary technical team spanning Platform Engineering Data Engineering Data Product Enablement and Site Reliability Engineering.
- Set clear technical direction and accountability across the team and develop senior technical talent capable of owning major platform capabilities and engineering domains.
- Balance engineering capacity across platform development reliability technical debt automation operational improvement reusable capabilities and targeted data product enablement.
- Lead the architecture and implementation of Azure Databricks capabilities including workspaces compute jobs Delta Lake Unity Catalog data sharing platform security and enterprise deployment patterns.
- Define Azure integration patterns for identity networking private connectivity storage secrets security controls monitoring logging and shared enterprise services.
- Own the technical governance architecture for the platform including Unity Catalog standards permissions access patterns lineage ownership data sharing and policy enforcement in partnership with Cybersecurity and enterprise governance teams.
- Establish scalable platform engineering practices including Infrastructure as Code Terraform CI/CD automated testing environment management configuration management deployment automation and reusable engineering components.
- Lead the development of API-driven and automated self-service platform capabilities that allow domain teams to onboard provision environments request access deploy workloads and publish governed data products efficiently.
- Establish golden paths reusable platform services engineering standards and reference implementations that allow data product teams to deliver consistently without unnecessary central dependency.
- Establish and continuously improve the platform operating model including observability reliability objectives incident and problem management resilience recovery performance capacity and operational automation.
- Ensure the platform provides appropriate monitoring service health visibility cost transparency usage metrics and operational reporting.
- Apply a strong cost and value mindset across Azure and Databricks consumption platform services licensing capacity and engineering investments.
- Establish FinOps practices including consumption visibility cost allocation workload optimization capacity forecasting and showback or chargeback where appropriate.
- Lead the hub-and-spoke technical operating model by establishing enterprise platform standards and shared capabilities while enabling domain teams to retain ownership of their business logic and data products.
- Work with less mature domain teams to accelerate onboarding and adoption through targeted enablement reusable patterns and technical support.
- Work with mature spokes and domain platforms as design partners identifying proven capabilities and engineering patterns that can be reused federated or adopted rather than unnecessarily rebuilt within the central platform.
- Drive technical interoperability across domains including common standards for data products sharing identity governance deployment observability and cross-domain integration.
- Partner with Enterprise Architecture to ensure alignment with enterprise technology principles and architecture governance while retaining technical architecture accountability for the Enterprise Data Platform.
- Partner with Analytics to ensure strong integration with Power BI and enterprise analytics capabilities while maintaining clear ownership boundaries between the platform and analytics functions.
- Partner with MDM Data Quality and Governance teams to provide the technical capabilities required for governance quality metadata stewardship lineage security and compliance without assuming ownership of those enterprise functions.
- Serve as HARMANs technical counterpart to implementation partners and systems integrators retaining architecture and engineering decision rights and reviewing major designs deliverables and technical decisions.
- Ensure external partners transfer platform knowledge source code Terraform automation documentation runbooks architecture decisions operational procedures and engineering capabilities to the internal HARMAN team.
- Build the internal technical capability required for HARMAN to operate support and evolve the platform as external implementation capacity ramps down.
- Manage platform technology vendors and service providers including technical performance delivery quality service levels dependencies and commercial considerations.
- Drive platform adoption by engaging with data product teams and domain leaders identifying friction measuring usage and service health and continuously improving platform capabilities.
- Support the rationalization and retirement of redundant or legacy data platform technologies as workloads transition to the strategic enterprise platform.
What You Need to Be Successful
- 8 years of experience in enterprise data platforms data engineering platforms cloud platforms or related technology environments with demonstrated technical leadership responsibility.
- Experience leading technical teams responsible for platform engineering data engineering reliability or enterprise data services.
- Strong experience with Microsoft Azure and Azure Databricks in enterprise production environments.
- Strong understanding of Azure Databricks architecture including workspaces compute jobs and workflows Delta Lake Unity Catalog data sharing platform security and enterprise deployment patterns.
- Strong understanding of Microsoft Azure architecture including identity networking private connectivity storage secrets management security monitoring and integration with enterprise services.
- Demonstrated experience owning architecture decisions technical standards and platform evolution for a production enterprise platform.
- Experience with Unity Catalog including catalog architecture permissions identity and access patterns technical governance lineage ownership and data sharing.
- Strong experience with Infrastructure as Code and platform automation using technologies such as Terraform.
- Experience with DevOps and DataOps practices including CI/CD Azure DevOps or GitHub automated testing automated provisioning deployment automation environment management and configuration management.
- Experience designing or operating self-service platform capabilities for engineering or data teams.
- Experience establishing engineering standards golden paths reusable services templates and reference architectures.
- Strong understanding of platform reliability and operations including observability monitoring incident and problem management resilience disaster recovery performance capacity and service-level expectations.
- Understanding of cloud economics and FinOps principles including consumption monitoring cost allocation workload optimization showback or chargeback and capacity forecasting.
- Experience working within federated hub-and-spoke or similarly distributed data and technology operating models.
- Experience enabling domain engineering teams within enterprise standards and guardrails without unnecessarily centralizing delivery.
- Experience leading and developing senior engineers and building distributed technical ownership within a team.
- Experience managing systems integrators implementation partners or major technology vendors including technical oversight architecture review knowledge transfer and transition to internal ownership.
- Strong stakeholder management skills with the ability to work effectively across engineering architecture cybersecurity analytics AI infrastructure governance business domains procurement and senior leadership.
- Ability to make clear technical and investment trade-offs across architecture engineering complexity reliability security cost delivery speed technical debt and business value.
- Strong communication and decision-making skills with the ability to communicate technical direction architecture decisions risks and trade-offs to both technical teams and senior business leaders.
Bonus Points if You Have
- Previous experience as a Data Platform Lead Data Platform Engineering Manager Data Engineering Manager Lead Data Architect Cloud Platform Lead or similar enterprise technical leadership role.
- Deep experience operating Azure Databricks as a strategic enterprise data platform.
- Experience with advanced Unity Catalog capabilities Delta Sharing workspace architecture compute policies serverless capabilities and enterprise-scale governance patterns.
- Experience with Databricks Asset Bundles Databricks repositories deployment patterns and CI/CD integration.
- Experience with Spark architecture workload optimization cluster and compute management and large-scale data engineering patterns.
- Familiarity with MLflow model lifecycle management feature engineering or other Databricks AI and ML platform capabilities.
- Experience implementing API-driven self-service provisioning for workspaces environments access infrastructure and platform services.
- Experience establishing SRE practices including SLOs SLIs observability recovery automation reliability engineering and operational readiness.
- Experience building or operating platform capabilities that support governed enterprise data products.
- Experience working with mature domain engineering organizations as design partners in a federated enterprise model.
- Experience with enterprise data sharing and cross-domain interoperability patterns.
- Experience leading the transition from externally implemented technology platforms to internally owned engineering and operations teams.
- Experience supporting the rationalization or migration of legacy data warehouses data platforms ETL technologies or analytics environments.
- Knowledge of software engineering best practices applied to data platform engineering and data product delivery.
- Relevant certifications in Microsoft Azure Databricks cloud architecture data engineering or related technical disciplines.
What Makes You Eligible
- Ability to work from an office in Novi MI 3 days per week (hybrid)
- Successfully complete a background investigation and drug screen as a condition of employment
What We Offer
- Access to employee discounts on world-class products including JBL HARMAN Kardon AKG and more
- Extensive training opportunities through our own HARMAN University
- Competitive wellness benefits
- Tuition reimbursement
- Be Brilliant employee recognition and rewards program
- An inclusive and diverse work environment that fosters and encourages professional and personal development
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Salary Ranges:
HARMAN is proud to be an Equal Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard torace religion color national origin gender (including pregnancy childbirth or related medical conditions) sexual orientation gender identity gender expression age status as a protected veteran status as an individual with a disability or other applicable legally protected characteristics.
About Company
Symphony Teleca Corporation is the world’s first services company dedicated exclusively to helping clients manage the global convergence of software, the cloud and connected devices. We deliver solutions for product and services innovation, with contemporary product development, syste ... View more