We are looking for a colleague to lead our Data Engineering team which is responsible for developing and maintaining both our on-premise Data Warehouse and our Microsoft Azure-based Cloud Data Platform. The team enables a wide range of business-critical data solutions across the Ignitis Group - including sales financial operational customer smart metering and energy insights - ensuring reliable and scalable data foundations for the entire organization. If that speaks to you wed be happy to welcome you to our team!
Take YOUR part in #EnergySmart!
You will contribute to the creation of a green and secure energy ecosystem by:
- Leading a team of data engineers - guiding mentoring supporting career growth and managing performance
- Owning end-to-end delivery of data solutions - ensuring on-time delivery while maintaining high quality and engineering best practices
- Setting technical excellence - establishing data architecture and engineering standards to ensure data quality reliability and scalability
- Staying current with emerging trends and best practices in data engineering and introducing relevant improvements
- Collaborating with cross-functional stakeholders to translate business needs into robust and scalable data solutions
Qualifications :
- 5 years of experience in a hands-on data engineering role
- 2 years of experience leading a team of engineers - including mentoring coaching and performance management
- Ability and motivation to remain technical and provide architectural and delivery guidance when needed
- Strong sense of ownership resilience and a proactive problem-solving mindset
- Proven track record in establishing and improving engineering practices development processes and operational excellence
- Solid knowledge of data modeling ETL/ELT pipelines data warehousing concepts and workflow orchestration
- Excellent Python and SQL skills
Would be an advantage:
- Experience with Microsoft Azure services ideally including Microsoft Fabric
- Familiarity with modern Cloud Data Platforms such as Databricks Snowflake or similar solutions
- Experience with data streaming technologies such as Apache Kafka Apache Pulsar or similar
Additional Information :
- A package of additional benefits to choose from: pension accumulation health insurance or another benefit from the selectable benefits list in the MELP application
- Additional paid days for health improvement short-term illness volunteering and accumulated work experience
- A hybrid work model (32) and flexible working hours
- Internal career opportunities
- Extensive learning and qualification enhancement programs
- Mentorship-based culture designed to facilitate meaningful and value-driven work
- Take part in an unfolding energy transformation process to create a 100% green and secure energy ecosystem for both current and future generations
Join a growing and increasingly international team of energy smart people united by a common purpose. We all play our part in creating a 100% green and secure energy ecosystem for current and future generations.
And the way to achieve this is certainly not to wait for the perfect moment. We believe that the power to act comes from the charge we bring to our work every day. United by purpose. Owning the challenge. Passion for reinvention. Pursuing excellence. These are our mindsets. Together they yield the energy that drives everything we do. The energy generated by our choices. If you are guided by the same mindsets we look forward to welcoming you to our team!
As we pursue our strategic goals to increase gender balance in Ignitis Group we are indicating f/m/d next to job titles meaning we welcome candidates of all genders female male or diverse.
Ignitis Group ensures equal opportunities. We welcome all applicants and do not discriminate against race religion gender sexual orientation or gender identity age disability or other personal traits unrelated to work obligations.
Remote Work :
No
Employment Type :
Full-time
We are looking for a colleague to lead our Data Engineering team which is responsible for developing and maintaining both our on-premise Data Warehouse and our Microsoft Azure-based Cloud Data Platform. The team enables a wide range of business-critical data solutions across the Ignitis Group - incl...
We are looking for a colleague to lead our Data Engineering team which is responsible for developing and maintaining both our on-premise Data Warehouse and our Microsoft Azure-based Cloud Data Platform. The team enables a wide range of business-critical data solutions across the Ignitis Group - including sales financial operational customer smart metering and energy insights - ensuring reliable and scalable data foundations for the entire organization. If that speaks to you wed be happy to welcome you to our team!
Take YOUR part in #EnergySmart!
You will contribute to the creation of a green and secure energy ecosystem by:
- Leading a team of data engineers - guiding mentoring supporting career growth and managing performance
- Owning end-to-end delivery of data solutions - ensuring on-time delivery while maintaining high quality and engineering best practices
- Setting technical excellence - establishing data architecture and engineering standards to ensure data quality reliability and scalability
- Staying current with emerging trends and best practices in data engineering and introducing relevant improvements
- Collaborating with cross-functional stakeholders to translate business needs into robust and scalable data solutions
Qualifications :
- 5 years of experience in a hands-on data engineering role
- 2 years of experience leading a team of engineers - including mentoring coaching and performance management
- Ability and motivation to remain technical and provide architectural and delivery guidance when needed
- Strong sense of ownership resilience and a proactive problem-solving mindset
- Proven track record in establishing and improving engineering practices development processes and operational excellence
- Solid knowledge of data modeling ETL/ELT pipelines data warehousing concepts and workflow orchestration
- Excellent Python and SQL skills
Would be an advantage:
- Experience with Microsoft Azure services ideally including Microsoft Fabric
- Familiarity with modern Cloud Data Platforms such as Databricks Snowflake or similar solutions
- Experience with data streaming technologies such as Apache Kafka Apache Pulsar or similar
Additional Information :
- A package of additional benefits to choose from: pension accumulation health insurance or another benefit from the selectable benefits list in the MELP application
- Additional paid days for health improvement short-term illness volunteering and accumulated work experience
- A hybrid work model (32) and flexible working hours
- Internal career opportunities
- Extensive learning and qualification enhancement programs
- Mentorship-based culture designed to facilitate meaningful and value-driven work
- Take part in an unfolding energy transformation process to create a 100% green and secure energy ecosystem for both current and future generations
Join a growing and increasingly international team of energy smart people united by a common purpose. We all play our part in creating a 100% green and secure energy ecosystem for current and future generations.
And the way to achieve this is certainly not to wait for the perfect moment. We believe that the power to act comes from the charge we bring to our work every day. United by purpose. Owning the challenge. Passion for reinvention. Pursuing excellence. These are our mindsets. Together they yield the energy that drives everything we do. The energy generated by our choices. If you are guided by the same mindsets we look forward to welcoming you to our team!
As we pursue our strategic goals to increase gender balance in Ignitis Group we are indicating f/m/d next to job titles meaning we welcome candidates of all genders female male or diverse.
Ignitis Group ensures equal opportunities. We welcome all applicants and do not discriminate against race religion gender sexual orientation or gender identity age disability or other personal traits unrelated to work obligations.
Remote Work :
No
Employment Type :
Full-time
View more
View less