Data Platform Engineering Manager
Reads like a Data Leadership role: running a data team.
Pune-Maharashtra-India
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingIn this role, you will lead a data platform engineering team, working closely with US-based peers and leadership, with shared responsibility for designing and operating the platform's core data layer: Kafka and Flink streaming pipelines, Spark data processing, the Apache Iceberg lakehouse, and time-series storage.
Lead the design, delivery, and evolution of the OBDP data platform architecture, including streaming, storage, and lakehouse layers.
You will own your outcomes with accountability, safety, and integrity, making clear decisions and following through on commitments.
Manage a team of 3-5 data platform engineers, including hiring, performance management, and career development.
From the employer’s posting
In this role, you will lead a data platform engineering team, working closely with US-based peers and leadership, with shared responsibility for designing and operating the platform's core data layer: Kafka and Flink streaming pipelines, Spark data processing, the Apache Iceberg lakehouse, and time-series storage. You will shape the team's roadmap through PI planning, improve engineering and operational practices, and ensure the platform can support both current tenants and future growth.
Key Responsibilities Lead the design, delivery, and evolution of the OBDP data platform architecture, including streaming, storage, and lakehouse layers. Manage a team of 3-5 data platform engineers, including hiring, performance management, and career development.
How You Will Do It You will own your outcomes with accountability, safety, and integrity, making clear decisions and following through on commitments. You will stay close to the work, remove obstacles quickly, and keep priorities focused on what delivers the most value to customers and application teams.
Lead the design, delivery, and evolution of the OBDP data platform architecture, including streaming, storage, and lakehouse layers. Manage a team of 3-5 data platform engineers, including hiring, performance management, and career development. Partner with product management on the roadmap and PI planning, coordinating dependencies with application teams, SRE teams, and product stakeholders.
What you’ll bring
All qualificationsCore experience
- Bachelor's degree in computer science, Engineering, Data Science, or a related technical field.
- Experience leading large data migrations, such as warehouse-to-lakehouse cutovers.
- 10+ years of experience in software engineering, data engineering, or platform engineering, including 3+ years leading engineering teams.
- Experience with IoT, telemetry, or real-time data such as building automation, energy, or BMS.
- Experience managing teams in India that collaborate closely with US-based counterparts, with responsibility for delivery, quality, and team development.
- Strong knowledge of event-driven data pipelines and streaming frameworks such as Kafka and Flink.
Preferred experience
- Experience designing and operating cloud-native data platforms, with Azure preferred.
Qualification wording
Bachelor's degree in computer science, Engineering, Data Science, or a related technical field.
Experience leading large data migrations, such as warehouse-to-lakehouse cutovers.
10+ years of experience in software engineering, data engineering, or platform engineering, including 3+ years leading engineering teams.
Experience with IoT, telemetry, or real-time data such as building automation, energy, or BMS.
Experience managing teams in India that collaborate closely with US-based counterparts, with responsibility for delivery, quality, and team development.
Strong knowledge of event-driven data pipelines and streaming frameworks such as Kafka and Flink.
Experience designing and operating cloud-native data platforms, with Azure preferred.
Tools in this posting
- Azure
- Datadog
- Delta Lake
- Grafana
- Iceberg
- Kafka
- Kubernetes
- PostgreSQL
- Snowflake
- Terraform
- Trino
Source — Tool mentions in context
- Guide time-series and operational storage patterns, including TimescaleDB, PostgreSQL, and Iceberg. - Ensure reliable deployment and operations on Azure, including AKS, CI/CD, infrastructure as code, and multi-region rollouts. - Improve observability, reliability, and performance, with clear SLOs and root cause analysis.
- Hands-on understanding of Spark, lakehouse table formats (Apache Iceberg, Delta Lake, or Hudi), data warehouses such as Snowflake, and time-series storage. - Experience designing and operating cloud-native data platforms, with Azure preferred. - Experience with data governance, security, encryption, access control, and compliance in enterprise environments.
- Experience with IoT, telemetry, or real-time data such as building automation, energy, or BMS. - Exposure to Trino, GraphQL, or Datadog, Prometheus, and Grafana. - Background in SaaS or multi-tenant platform design.
- Strong knowledge of event-driven data pipelines and streaming frameworks such as Kafka and Flink. - Hands-on understanding of Spark, lakehouse table formats (Apache Iceberg, Delta Lake, or Hudi), data warehouses such as Snowflake, and time-series storage. - Experience designing and operating cloud-native data platforms, with Azure preferred.
Role Overview In this role, you will lead a data platform engineering team, working closely with US-based peers and leadership, with shared responsibility for designing and operating the platform's core data layer: Kafka and Flink streaming pipelines, Spark data processing, the Apache Iceberg lakehouse, and time-series storage. You will shape the team's roadmap through PI planning, improve engineering and operational practices, and ensure the platform can support both current tenants and future growth. Key Responsibilities
- Define standards for data modeling, partitioning, retention, lifecycle management, access control, and data quality. - Guide time-series and operational storage patterns, including TimescaleDB, PostgreSQL, and Iceberg. - Ensure reliable deployment and operations on Azure, including AKS, CI/CD, infrastructure as code, and multi-region rollouts.
- Partner with product management on the roadmap and PI planning, coordinating dependencies with application teams, SRE teams, and product stakeholders. - Oversee event-driven pipelines on Kafka and Flink and batch and incremental processing on Spark. - Define standards for data modeling, partitioning, retention, lifecycle management, access control, and data quality.
- Experience managing teams in India that collaborate closely with US-based counterparts, with responsibility for delivery, quality, and team development. - Strong knowledge of event-driven data pipelines and streaming frameworks such as Kafka and Flink. - Hands-on understanding of Spark, lakehouse table formats (Apache Iceberg, Delta Lake, or Hudi), data warehouses such as Snowflake, and time-series storage.
- Experience with data governance, security, encryption, access control, and compliance in enterprise environments. - Familiarity with Kubernetes, CI/CD, and infrastructure as code tools such as Terraform or Bicep. - Experience planning and delivering in a scaled agile (SAFe/PI planning) environment.
Posting record
Report an errorActively hiringFirst seen by us 8 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 21, 2026 · 8 days ago
- Recorded sightings
- 6
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
Engineering Manager, Data Platform
Johnson Controls is seeking an Engineering Manager to lead the India-based engineers of the data platform team within the OpenBlue Data Platform (OBDP). The team owns the streaming, storage, and lakehouse foundation that carries building telemetry and operational data for OpenBlue's smart-building applications. This role partners closely with the Data Platform Engines team, application teams, SRE, security, and product to deliver a reliable, scalable, and secure data foundation.
Role Overview
In this role, you will lead a data platform engineering team, working closely with US-based peers and leadership, with shared responsibility for designing and operating the platform's core data layer: Kafka and Flink streaming pipelines, Spark data processing, the Apache Iceberg lakehouse, and time-series storage. You will shape the team's roadmap through PI planning, improve engineering and operational practices, and ensure the platform can support both current tenants and future growth.
Key Responsibilities
- Lead the design, delivery, and evolution of the OBDP data platform architecture, including streaming, storage, and lakehouse layers.
- Manage a team of 3-5 data platform engineers, including hiring, performance management, and career development.
- Partner with product management on the roadmap and PI planning, coordinating dependencies with application teams, SRE teams, and product stakeholders.
- Oversee event-driven pipelines on Kafka and Flink and batch and incremental processing on Spark.
- Define standards for data modeling, partitioning, retention, lifecycle management, access control, and data quality.
- Guide time-series and operational storage patterns, including TimescaleDB, PostgreSQL, and Iceberg.
- Ensure reliable deployment and operations on Azure, including AKS, CI/CD, infrastructure as code, and multi-region rollouts.
- Improve observability, reliability, and performance, with clear SLOs and root cause analysis.
- Drive adoption of SDLC best practices across the team, including code review standards, branching and release strategy, automated testing, and secure coding.
- Promote effective use of AI-assisted development (Claude Code, GitHub Copilot, or similar) with sound review practices.
- Mentor engineers and strengthen team capability through coaching, code review, design review, and knowledge sharing.
How You Will Do It
- You will own your outcomes with accountability, safety, and integrity, making clear decisions and following through on commitments.
- You will stay close to the work, remove obstacles quickly, and keep priorities focused on what delivers the most value to customers and application teams.
- You will improve every day by using data, candid feedback, and structured problem-solving to simplify processes and strengthen the platform.
- You will win as one team by building trust across engineering, product, SRE, security, and across US and India time zones, and by valuing diverse perspectives.
- You will set clear technical standards and help the team execute them consistently across design, build, and operations.
- You will balance strategy with hands-on leadership, ensuring architecture decisions translate into reliable delivery and measurable results.
Qualifications
- Bachelor's degree in computer science, Engineering, Data Science, or a related technical field.
- 10+ years of experience in software engineering, data engineering, or platform engineering, including 3+ years leading engineering teams.
- Experience managing teams in India that collaborate closely with US-based counterparts, with responsibility for delivery, quality, and team development.
- Strong knowledge of event-driven data pipelines and streaming frameworks such as Kafka and Flink.
- Hands-on understanding of Spark, lakehouse table formats (Apache Iceberg, Delta Lake, or Hudi), data warehouses such as Snowflake, and time-series storage.
- Experience designing and operating cloud-native data platforms, with Azure preferred.
- Experience with data governance, security, encryption, access control, and compliance in enterprise environments.
- Familiarity with Kubernetes, CI/CD, and infrastructure as code tools such as Terraform or Bicep.
- Experience planning and delivering in a scaled agile (SAFe/PI planning) environment.
- Strong communication skills with the ability to align technical teams and business stakeholders.
Nice to Have
- Experience leading large data migrations, such as warehouse-to-lakehouse cutovers.
- Experience with IoT, telemetry, or real-time data such as building automation, energy, or BMS.
- Exposure to Trino, GraphQL, or Datadog, Prometheus, and Grafana.
- Background in SaaS or multi-tenant platform design.
Source details
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- Pay
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- Location & working pattern
Pune-Maharashtra-India
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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