Senior Data Engineer (Snowflake/Databricks)
Offer summary

(Summary generated by AI based on the full job description)

Project migrates data and reporting from a legacy estate to a modern platform built on Databricks and Microsoft Fabric. Key skills required: Advanced SQL, Python, Snowflake/Databricks, Apache Spark (PySpark), DBT, Airflow/Dagster and cloud experience (AWS/Azure). Responsibilities include developing, optimizing and maintaining the data warehouse, designing ETL/ELT, dimensional modeling, database administration and performance tuning, automating processes, building analytical tools and implementing monitoring, governance and security.

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Senior Data Engineer (Snowflake/Databricks)

Company: DataArt Poland sp. z o.o.

from: 17 September 2026
to: 17 October 2026
22 000 - 26 700net (+ VAT)/ mth.B2B contract (full-time)
18 000 - 21 800gross/ mth.contract of employment
Offer parameters
level:senior
working mode:remote • hybrid • full office
location:Warszawa, Masovian
Warszawa, Masovian

Requirements

Expected technologies

Snowflake Data Cloud
Databricks
Python
SQL
Apache Spark
PyTorch

Optional technologies

Apache Flink
Terraform
Kubernetes
Docker
Apache Hive
AWS
Microsoft Azure
Apache Airflow
Kafka
Debian

Our requirements

  • 5+ years of experience or 5+ completed projects
  • Advanced SQL and query optimization, with proficiency across popular database variations
  • Python for data engineering and automation
  • Cloud data platforms: Snowflake and/or Databricks
  • Cloud services: AWS and/or Azure
  • Data transformation and modeling with DBT
  • ETL/ELT pipeline design, development, and maintenance
  • Apache Spark (PySpark preferred)
  • Workflow orchestration using Apache Airflow, Dagster, or another widely adopted orchestrator
  • Relational database design and performance tuning (PostgreSQL, MySQL, SQL Server, Oracle, etc.)
  • Data warehousing concepts and dimensional modeling
  • Data management fundamentals: data modeling, data quality, metadata management, data warehouse/lake patterns, distributed systems
  • Version control using Git and CI/CD practices
  • Data governance, data quality, lineage, and observability practices
  • Security and access control implementation in cloud data platforms

Optional

  • Apache Kafka, Apache Flink, Apache Beam
  • Terraform, Kubernetes, Docker
  • Apache Iceberg, Delta Lake, or Apache Hudi
  • Real-time and event-driven architectures
  • AWS Glue, Amazon MWAA, Azure Data Factory
  • Data Mesh and Data Product concepts
  • Machine learning data pipelines, feature stores, or AI development experience
  • Streaming analytics and Change Data Capture (CDC) solutions (e.g., Debezium)

Your responsibilities

  • Develop, operate, optimize, test, and maintain the data warehouse, including ETL/ELT process development, cube development, database/performance administration, and dimensional table design
  • Drive the full life-cycle of back-end development for the data warehouse
  • Identify, design, and implement internal process improvements - redesigning infrastructure for scalability, optimizing data delivery, and automating manual processes
  • Define data retention policies
  • Build analytical tools that leverage the data pipeline to deliver actionable insight into key business metrics (operational efficiency, customer acquisition, etc.)
  • Select and integrate tools for monitoring, managing, alerting on, and improving database performance
  • Develop and implement automated processes to ensure uninterrupted database updates and correction of vulnerabilities
  • Assemble large, complex datasets that meet functional and non-functional business requirements

About the project

The project migrates data and reporting from a legacy estate onto a modern platform built on Databricks and Microsoft Fabric. Quality engineering is central to the project. The business needs confidence that migrated data reconciles with the source, that pipelines behave as specified, and that reports produce consistent results.

This is how we organize our work

This is how we work

you focus on a single project at a timeyou focus on product developmentagile

Team members

1-10 people:backend developertechnical leaderdevOpsdata scientistautomated test programmer

This is how we work on a project

  • Continuous Integration

Development opportunities we offer

  • mentoring
  • technical knowledge exchange within the company

DataArt Poland sp. z o.o.

Our client is a UK financial services group operating in a highly regulated environment, currently rebuilding its data and analytics capability as part of a wider platform modernisation programme.
Senior Data Engineer (Snowflake/Databricks)
18k–21.8k zł / mth. (CoE), 22k–26.7k zł / mth. (B2B)
I apply to:
DataArt Poland sp. z o.o.
Warszawa, Masovian

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