Big Data - Platform Manager

Artificial Intelligence & Machine Learning

We’re a global, multi-disciplinary team that’s putting the innovative power of technology to work and transforming tomorrow. At HARMAN Automotive, we give you the keys to fast-track your career.

We are looking for a Big Data Platform Manager to lead the development, operation, and continuous improvement of our enterprise Data & Analytics platform. This role is responsible for enabling data product teams, analysts, engineers, and business users to deliver high-quality data and analytics solutions efficiently, securely, and at scale.

You will manage the platform capabilities, tooling, standards, and operating model that support modern data delivery, including cloud data platforms, data engineering environments, analytics work spaces, CI/CD, automated testing, monitoring, governance, and self‑service capabilities.

The role combines a strong technical understanding of modern data platforms with leadership, stakeholder management, product‑oriented thinking, and the ability to manage a team of up to 5 platform engineers.

• Own the roadmap for the enterprise Data & Analytics platform, ensuring alignment with business priorities, data strategy, architecture standards, and security requirements.
• Define and manage platform capabilities that enable data product teams to build, test, deploy, monitor, and operate data solutions efficiently.
• Partner with data engineering, analytics, architecture, security, infrastructure, transformation and business teams to continuously improve the platform experience for developers as well as end users.
• Act as the product owner or service owner for D&A platform services, balancing feature development, operational reliability, cost management, and user needs.
• Manage the D&A platform like a product—clear roadmap, backlog, users, and measurable outcomes; balance speed, stability, cost and experience.
• E2E Platform operations ownership - Manage incidents, changes, SLAs, and ensure reliability at scale.
• Oversee platform support processes, incident management, service requests, change management, and operational monitoring.
• Lead the development of automated provisioning capabilities for D&A work spaces, environments, data product teams, and project resources.
• Apply a cost & value mindset to optimize Fabric capacity, Databricks usage, and overall platform cost vs. value.
• Develop platform capabilities that help data engineering and analytics teams work more efficiently, including automated testing, CI/CD pipelines, deployment automation, code quality checks, and reusable templates.
• Ensure the platform supports data governance, access control, privacy, security, lineage, metadata management, and compliance requirements.
• Lead, coach, and develop a team of platform engineers, Dev Ops specialists, and support analysts, target users of the platform.

• 7+ years of experience in managing or leading Data & Analytics platforms, data engineering platforms, cloud platforms, or related technology services.
• Strong understanding of modern data architecture, including data lakes, data warehouses, lake houses, data pipelines, orchestration, and analytics tooling.
• Experience with MS Azure / MS Fabric cloud platforms and services.
• Experience with Dev Ops, Data Ops, CI/CD (Azure Dev Ops / Git Hub Actions), infrastructure-as-code, automated testing, deployment automation, and monitoring practices.
• Familiarity with One Lake architecture, workspace topology, and capacity (F‑SKU) planning, data loading patterns and orchestration processes.
• Familiarity with data platform technologies such as Databricks, Snowflake, Big Query, Synapse, Redshift, dbt, Airflow, Azure Data Factory, Kafka, or similar tools.
• Understanding of data governance, security, access management, metadata, lineage, and compliance principles.
• Strong stakeholder management, communication, prioritization, and problem‑solving skills.
• Experience working with agile delivery methods and product management practices.

• Previous experience as a Data Platform Manager, Analytics Platform Lead, Data Engineering…