Build and maintain data pipelines using Python, Airflow, and Microsoft Fabric
Integrate data from diverse sources (on-prem, cloud, APIs) into a unified data platform
Implement and improve lakehouse/warehouse data models and transformation layers
Support data quality, monitoring, security, and governance across pipelines and storage
Collaborate with senior engineers, analysts, and business stakeholders to deliver data solutions

Jobs at Ignitis Group

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About the role

Job Description Ignitis Group is seeking a Data Engineer to join the Data Engineering Team and help develop data solutions on a cloud-based Microsoft Fabric data platform. This role focuses on building and maintaining reliable, scalable data pipelines to support energy data across the organization, including sales, financial, technical, people, and smart metering data.

Responsibilities

Qualifications:

Build and maintain data pipelines using Python, Airflow, and Microsoft Fabric
Integrate data from diverse sources (on-prem, cloud, APIs) into a unified data platform
Implement and improve lakehouse/warehouse data models and transformation layers
Support data quality, monitoring, security, and governance across pipelines and storage
Collaborate with senior engineers, analysts, and business stakeholders to deliver data solutions
Participate in solution design discussions and production rollouts
Continuously improve pipelines, performance, and data reliability
2–4 years of experience in data engineering or related role
Strong SQL and Python skills
Solid understanding of ETL/ELT, data modeling, and warehouse/lakehouse concepts
Experience building data pipelines using orchestration tools (Airflow)
Awareness of data quality, security, and governance best practices
Ability to work independently while collaborating within a team
Motivation to learn, grow technically, and take increasing ownership over time
Nice-to-have: Experience with Microsoft Fabric and/or Microsoft Azure; exposure to data governance or data cataloging tools; experience with large-s

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Key requirements

Build and maintain data pipelines using Python, Airflow, and Microsoft Fabric
Integrate data from diverse sources (on-prem, cloud, APIs) into a unified data platform
Implement and improve lakehouse/warehouse data models and transformation layers
Support data quality, monitoring, security, and governance across pipelines and storage
Collaborate with senior engineers, analysts, and business stakeholders to deliver data solutions