Role Summary

You own pipelines end to end: ingestion to modeled warehouse, deployed through CI/CD, monitored, and cost-aware. Projects vary - a lakehouse on one engagement, a classic warehouse on the next - so you work from principles, not from one platform's playbook. Data engineering is your profession, not a side skill picked up on a backend project - and you explain your decisions to engineers and stakeholders alike.

The Mission

Build reliable, transparent, cost-effective data pipelines and help clients understand the value behind our technical choices.

The Tech Stack

• Core Languages: Python (OOP, typing, testing), SQL (advanced). Scala welcome.

• Platforms: Databricks, Snowflake, BigQuery, Synapse, Redshift.

• Orchestration: Airflow or Azure Data Factory; Dagster.

• Transformation: dbt (Core/Cloud), Spark/PySpark (optimization focus).

• Streaming: Kafka, Kinesis, or Event Hubs (working basics).

• Infrastructure: Terraform, Docker, Kubernetes basics, CI/CD.

Your Skills

• Experience: 2+ years of hands-on data engineering (ETL/ELT in production).

• Data Architecture: star/snowflake schemas, SCD, Medallion architecture, and the working vocabulary of the craft: idempotency, backfills, late-arriving data, batch vs streaming trade-offs.

• Key Platforms: proven experience with Databricks (clusters, jobs, Delta) or Snowflake; orchestration with Airflow or ADF.

• Engineering Core: Python (OOP, tests) and SQL for complex transformations - including reading query plans.

• Cloud Fluency: one major cloud and its data services (Kinesis/Lambda, Dataflow/BigQuery, Synapse).

• Infrastructure: Terraform - deploy and modify resources independently.

• Data Quality: dbt tests or Great Expectations in practice; you monitor what you ship.

• Communication: explain technical decisions to clients and the team.

Your Responsibilities

• Design and build pipelines: ingest, clean, transform into lakes and warehouses.

• Optimize for performance and cost - know a working query from an efficient one (FinOps).

• Deploy through CI/CD and Terraform; keep environments reproducible.

• Implement quality checks and freshness monitoring; alert before the client notices.

• Clarify requirements with stakeholders; review and guide Junior engineers.

Nice to Have

• Advanced IaC: complex Terraform or Pulumi modules.

• Lakehouse Formats: Delta Lake or Iceberg internals - time travel, schema evolution.

• Streaming: a production streaming pipeline you built or maintained.

• NoSQL: data modeling for MongoDB or DynamoDB.

• Certifications: associate level (Azure Data Engineer, Databricks Certified DE).

What we offer

• Long-term career stability with a competitive salary paid in USD.

• Conditions for steady career development.

• Development supported by dedicated mentors and a variety of programs focused on expertise and innovation.

• Private medical insurance provided after successful completion of the probationary period

• A well-equipped and cozy office supports comfort and productivity across all project stages.

• Welcoming atmosphere and a friendly corporate culture.

If you feel this opportunity resonates with you, apply now — we’re looking forward to getting to know you!