Senior Data Engineer
Build tested, monitored pipelines and lakehouses for clients in Europe, North America and the Gulf, in their repositories and their cloud.
About the role
You design and build data pipelines and lakehouse layers for DATAI’s clients, working in their repositories, tickets and stand-ups. A senior architect reviews your merge requests, and you review other engineers’.
Projects and stack
Client data platforms on AWS, Azure or Google Cloud. A project usually starts from the written plan agreed in our assessment: move a warehouse off a legacy system, add streaming to a batch platform, or put tests and monitoring on pipelines nobody trusts any more.
You build in the client’s cloud and use the tools it already runs where they fit. The ones you’ll meet most often are Airflow, dbt, Spark, Kafka and Fivetran for pipelines, Databricks, Snowflake, Fabric and BigQuery for storage, and Terraform with GitHub Actions for infrastructure.
What you will do
- Build batch and streaming pipelines with Airflow, dbt, Spark and Kafka, or the tools the client already runs.
- Add schema, freshness and volume tests to every pipeline, and alerts that reach the owning team.
- Model bronze, silver and gold layers on Databricks, Snowflake or Fabric.
- Review other engineers’ merge requests on the project.
- Write the runbook and architecture diagram that let the client’s team run what you built.
- Demo working pipelines to the client every week.
What we look for
- A record of building data pipelines that run in production, and of fixing them when they fail.
- Strong SQL and Python, and experience with at least one orchestrator such as Airflow.
- Hands-on work with a cloud data platform on AWS, Azure or Google Cloud.
- Data modelling for analytics, and a view on when a dimensional model or medallion layers suit the job.
- Experience giving and receiving code review.
- Clear written English for client tickets, reviews and documentation, and enough spoken English to explain a design decision on a call.
Good to have
- Streaming with Kafka or Flink.
- Infrastructure as code with Terraform.
- Data quality tooling such as Great Expectations or Monte Carlo.
- Consulting or client-facing work.
How we work
You join the client’s daily stand-up and work in their repository and ticketing. You work in the US time zone, so stand-ups and reviews happen during the client’s business day.
A senior architect reviews every merge request before it merges. Tests and monitoring go in with the first pipeline, not at the end, and the runbook and architecture diagram are written while you build, so the client’s team can run the platform without us.
What we offer
You can work from Tashkent or remotely, and every project you join has a senior architect reviewing the code.
Apply
Send your CV and, if you have them, links to your profile or code.
- 1You applyYour details and CV go only to the DATAI hiring team.
- 2We read itAn engineer reviews every application.
- 3First interviewA call with an engineer about your experience and the projects we staff. Compensation is discussed here.
- 4Technical interviewA working session with one of our architects: SQL and Python on a realistic dataset, then the design of a pipeline for a client scenario, including how you would test and monitor it.
- 5OfferIf both sides want to go ahead, we send a written offer.