Staff Data Engineer: Lead Data Platform & Governance

Dkatalis

Jakarta Pusat

On-site

IDR 500,000,000 - 900,000,000

Full time

14 days+

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Job summary

DKatalis is seeking a seasoned engineering leader to own the design and evolution of our data infrastructure. You will define the technical roadmap for the data platform, mentor engineers in your squad, and drive cross-functional alignment to deliver high-impact digital products.

The role requires 10+ years in software/data engineering, strong English, and a proven track record deploying data models in production.

Qualifications

  • At least 10+ years of professional experience in software/data engineering.
  • Excellent written and spoken English.
  • Extensive track record of deploying and maintaining data models in production.
  • Strong knowledge of big data/distributed systems like Apache Kafka and Airflow.
  • Deep cloud data warehouse expertise (BigQuery or Redshift).
  • Proficiency in Python and modern software engineering practices.
  • Mentorship and coaching of engineers.
  • Experience with Lean/XP and CI/CD in Agile environments.
  • Pragmatic mindset balancing perfection with timely value.

Responsibilities

  • Lead the design and scaling of data infrastructure; oversee ETL pipelines (batch/streaming).
  • Define the technical roadmap of the data platform and drive cross-functional alignment.
  • Mentor engineers in the squad and promote best practices across teams.
  • Drive data governance, quality, and metadata standards.
  • Collaborate with Product and Engineering owners from concept to implementation.
  • Improve code quality and automation while balancing delivery speed.

Job description

DKatalis is seeking a seasoned engineering leader to own the design and evolution of our data infrastructure. You will define the technical roadmap for the data platform, mentor engineers in your squad, and drive cross-functional alignment to deliver high-impact digital products.

The role requires 10+ years in software/data engineering, strong English, and a proven track record deploying data models in production.

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