Data Engineer

About the Role

We're looking for two experienced Data Engineers to join a team building data infrastructure for a regulated financial environment. You'll design and evolve a configuration-driven data framework on Databricks and a Snowflake warehouse, and own the pipelines that run on top of it.

The pipelines you build have to stand up to scrutiny. They are auditable, lineage-aware, idempotent, and resilient, written in Python and PySpark with event-driven components such as Kafka, and covered by data quality controls that include testing, validation, monitoring, and alerting.

This is a senior role with real ownership. You'll make architectural decisions and defend the trade-offs, coach junior engineers, lead technical discussions and design reviews, and work with Product, Engineering, DevOps, and Regulatory teams to turn complex requirements into scalable designs that ship in incremental slices.

What You'll Do

• Design and evolve a configuration-driven data framework in Databricks and a Snowflake warehouse.
• Design, build, and optimize data pipelines using Databricks, Python, and PySpark, with event-driven components such as Kafka.
• Ensure pipelines are auditable, lineage-aware, idempotent, and resilient in regulated environments.
• Implement robust data quality controls, including testing, validation, monitoring, and alerting.
• Drive performance optimization across Spark and Snowflake workloads.
• Coach and mentor junior engineers, and lead technical discussions and design reviews.
• Partner with Product, Engineering, DevOps, and Regulatory teams to translate requirements into scalable technical designs.
• Contribute to the continuous improvement of development processes and tools.

What We're Looking For

• Experience as a software engineer, alongside hands-on data engineering experience, owning system design and delivery.
• Experience designing auditable, reproducible data pipelines in regulated or high-integrity environments using Python and PySpark.
• Ability to write and optimize complex SQL queries on large data sets.
• Strong data modeling and warehouse design fundamentals.
• Strong software engineering fundamentals: clean code, DRY, SOLID, automated testing, CI/CD, and observability, with a bias toward simple, maintainable solutions.
• Deep experience with a cloud lakehouse or data warehouse (Databricks, Snowflake, BigQuery, Redshift, EMR, or similar). The stack is Databricks and Snowflake; strong equivalent experience elsewhere transfers.
• Experience with a workflow orchestrator such as Airflow, Dagster, or Databricks Workflows.
• Proven system and platform design judgment: you own architectural decisions and can defend the trade-offs. Greenfield, scaling, and migration work all count.
• Comfort translating complex regulatory requirements into technical specifications.
• Ability to own large, ambiguous initiatives and deliver them in incremental, shippable slices.
• Strong communication and collaboration skills, including translating between technical and non-technical stakeholders.
• Nice to have: experience with event-driven architecture patterns.
• Nice to have: hands-on experience with AWS cloud infrastructure.
• Nice to have: practical experience with infrastructure as code, such as Terraform.
• Nice to have: experience modernizing legacy systems.
• Nice to have: FinTech, RegTech, or financial services background.

What We Offer

• Remote-first: work from anywhere in Serbia. The Belgrade office is optional.
• You'll work alongside engineers with 5–15 years of experience. No babysitting, just craft.
• Top-of-market salary for Serbia, paid in EUR, reviewed annually and tied to your impact.
• €1,500/year learning budget for conferences, courses, and books.
• 25 days PTO, flexible hours, and a culture that respects your time outside work.