Data engineer
You'll build and operate the data pipelines and platforms that power analytics, reporting, and AI at global scale.
About the role.
You'll build and operate the data pipelines and platforms that feed analytics, regulatory reporting, and AI workloads for enterprise clients - often moving petabyte-scale data out of legacy warehouses and into modern, governed platforms.
The work is unglamorous in the best way: data quality, lineage, and pipeline reliability, done well enough that the analysts and data scientists downstream never have to think about it.
Apply for this roleMultiple - Global
The shape of the work.
Design and build data pipelines
Build batch and streaming pipelines using tools like Spark, Kafka, and Airflow, with data quality and lineage built in from the start, not bolted on after.
Design data models clients can trust
Design warehouse and lakehouse schemas that hold up under real query load and evolve without breaking every downstream consumer.
Make data trustworthy
Implement the governance, cataloguing, and access-control layer that lets a client's analysts self-serve without a data engineer in the loop for every request.
What we're looking for.
3+ years in data engineering
Production experience building and operating pipelines at meaningful scale - not just prototypes.
SQL and a pipeline framework
Strong SQL plus hands-on experience with Spark, dbt, Airflow, or a comparable orchestration/transformation stack.
Cloud data platform depth
Experience with Snowflake, BigQuery, Databricks, or Redshift at production scale.
Streaming experience
Kafka or a comparable streaming platform, for clients moving from batch to near-real-time reporting.