Data Platform Engineer

• Build and maintain Kafka and Flink streaming jobs for ingestion and transformation.
• Develop and maintain Spark jobs for data processing tasks.
• Write unit and integration tests and contribute to CI pipelines.
• Fix production defects and support SIT, UAT, and deployments.
• Deploy and operate data services and jobs on AKS using Helm and Kubernetes operators.
• Build and maintain CI/CD pipelines and infrastructure as code.
• Set up monitoring, alerting, and dashboards for pipelines and services (Datadog, Azure Monitor, Prometheus, Grafana).
• Support routine database and lakehouse operations, including Iceberg table maintenance and PostgreSQL backups and tuning.

How You Will Do It

• Own the outcome with accountability by delivering well-tested features and following through on commitments.
• Stay close to work by understanding how the data you build is used downstream.
• Look for root causes, improve continuously, and raise issues with candor.
• Work as one team by partnering with engineers, QA, and product, sharing context, and asking for help early.
• Use clear documentation 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 software or data 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.
• Proficiency in Java, Scala, or Python, and solid SQL skills.
• Understanding of distributed systems basics such as partitioning, fault tolerance, and idempotency.
• Experience with Git, code review, and agile/Jira workflows.
  • Hands-on AI-assisted development with Claude Code, GitHub Copilot, or similar, with a critical eye for generated code.