Data Platform Engineer(Data & Devops)

About the job

Data Platform Engineer (Data & DevOps) At Johnson Controls, you will help build and operate the data platform behind OpenBlue, our smart-building platform. In this role, you will build and run the streaming and lakehouse pipelines that deliver trusted building and energy data to the applications our customers rely on. Role Overview We are looking for a Data Platform Engineer with 3+ years of experience to build, deploy, and operate pipelines on the OpenBlue Data Platform (OBDP). You will work with Kafka, Flink, Spark, Apache Iceberg, and Snowflake alongside senior engineers, and own how they run on Azure Kubernetes Service (AKS) through CI/CD, infrastructure as code, and observability. This is a hands-on role where you will own well-scoped features and platform operations end to end, from code to production, and take on more design ownership over time. Key Responsibilities

- Build and maintain Kafka and Flink streaming jobs for ingestion and transformation.

- Develop and maintain Spark jobs for data processing tasks.

- Collaborate with SRE to help manage infrastructure changes.

- Deploy and operate data services and jobs on AKS using Helm and Kubernetes operators.

- Set up monitoring, alerting, and dashboards for pipelines and services (Grafana).

- Support database and lakehouse operations, including Iceberg table maintenance and PostgreSQL backups and tuning.

- Build and maintain CI/CD pipelines and infrastructure as code (Terraform or Bicep).

- Automate environment promotion and deployments across dev, QA, SIT, UAT, and production.

- Support incident response and root cause analysis.

- Write unit and integration tests and fix production defects. How You Will Do It

- Own the outcome with accountability by delivering reliable pipelines and repeatable operations and following through on commitments.

- Stay close to work by understanding how the data you build is used downstream and how engineers deploy.

- Look for root causes, automate toil, improve continuously, and raise issues with candor.

- Work as one team by partnering with engineers, QA, SRE, and product, sharing context, and asking for help early.

- Use clear documentation, runbooks, and disciplined engineering practices to support consistency and handoffs. Qualifications

- Bachelor's degree in computer science, Information Technology, Engineering, or a related field.

- 3+ years of experience in data engineering, DevOps, or platform engineering.

- Hands-on experience with at least two of Kafka, Flink, Spark, Iceberg, or Snowflake, with working knowledge of or eagerness to learn the rest.

- Experience with Docker and Kubernetes, preferably AKS, including Helm.

- Experience building CI/CD pipelines and using infrastructure as code (Terraform or Bicep).

- Experience with monitoring and observability tools such as Datadog, Prometheus, or Grafana.

- Proficiency in .NET, Java, Scala, or Python, solid SQL, and scripting in Bash or similar.

- Understanding of distributed systems basics such as partitioning, fault tolerance, and idempotency.

- Hands-on AI-assisted development and automation with Claude Code, GitHub Copilot, or similar, with a critical eye for generated code. Nice to Have

- Production experience with Kubernetes operators for Flink, Spark, or Kafka.

- Experience with GitOps tools (Flux or Argo CD).

- Azure networking and security basics, including VNets, private endpoints, Key Vault, and Entra ID.

- Exposure to Trino, PostgreSQL, TimescaleDB, or HBase.

- Experience with Apache Airflow.

- Experience with time-series or IoT data.