Senior Data Engineer (Snowflake/Databricks)

Jobo; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

DataArt Poland is seeking a Senior Data Engineer to help migrate data and reporting from a legacy estate to a modern platform built on Databricks and Microsoft Fabric. You will collaborate with a cross-functional team to ensure high-quality data engineering, reliable pipelines, and consistent insights for a major UK financial services client.

Responsibilities include designing scalable data warehouses, optimizing ETL/ELT processes, and building dashboards and analytics tools.

Qualifications

• 5+ years of data engineering experience.
• Advanced SQL and Python for automation.
• Experience with Snowflake or Databricks and cloud platforms AWS or Azure.
• Strong knowledge of Spark, ETL/ELT, and Airflow.
• Understanding of data warehousing concepts and CI/CD practices.

Responsibilities

• Develop, optimize, and maintain data warehouse solutions, including complex ETL/ELT processes and dimensional table design.
• Drive the full life-cycle of back-end development and redesign infrastructure for improved scalability and automation.
• Build analytical tools that leverage data pipelines to deliver actionable insights into key business metrics.
• Select and integrate monitoring and alerting tools to ensure database performance and security.
• Assemble large, complex datasets that meet both functional and non-functional business requirements.

Skills

SQL

Python

ETL/ELT

Apache Spark

Apache Airflow

Data warehousing

Dimensional modeling

CI/CD

Databricks

Snowflake

AWS

Azure

Tools

Databricks

Snowflake

AWS

Azure

Job description

DataArt Poland is looking for a Senior Data Engineer to join a project focused on migrating data and reporting from a legacy estate to a modern platform built on Databricks and Microsoft Fabric. You will work within a cross-functional team to ensure high-quality data engineering, pipeline reliability, and consistent reporting for a major UK financial services client.

Key responsibilities

• Develop, optimize, and maintain data warehouse solutions, including complex ETL/ELT processes and dimensional table design.
• Drive the full life-cycle of back-end development and redesign infrastructure for improved scalability and automation.
• Build analytical tools that leverage data pipelines to deliver actionable insights into key business metrics.
• Select and integrate monitoring and alerting tools to ensure database performance and security.
• Assemble large, complex datasets that meet both functional and non-functional business requirements.

Requirements

• Over 5 years of experience or 5+ completed projects in data engineering roles.
• Advanced proficiency in SQL, query optimization, and Python for automation.
• Hands-on experience with cloud data platforms such as Snowflake or Databricks and cloud services like AWS or Azure.
• Strong knowledge of Apache Spark, ETL/ELT pipeline design, and workflow orchestration tools like Apache Airflow.
• Solid understanding of data warehousing concepts, dimensional modeling, and CI/CD practices.

What we offer

• Opportunity to work on a single, focused product development project within an agile environment.
• Access to professional mentoring and regular technical knowledge exchange sessions within the company.
• Engagement in a large-scale platform modernization program for a major financial services group.