Lead Data Engineer/Software Engineer with Data & AI Exposure - Sustainability Applications
Lead Data Engineer/Software Engineer with Data & AI Exposure - Sustainability Applications
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Job Description
We the IFS Sustainability Application team are looking for dynamic and openminded individuals to join us as Lead Data Engineer/Lead Software Engineer to work on sustainabilityrelated developments.
This is a great opportunity to work in the Sustainability and ESG (Environmental Social and Governance) sector where you will get the chance to develop products aimed at helping companies achieve their sustainability goals and report on their progress in line with international standards. The Sustainability product is in an incubation phase providing the opportunity to work on iterative product development consistent with a customercentric approach.
We are seeking a skilled and experienced Data Engineer with AI exposure or Software Engineer with Data & AI exposure. As a Lead Data Engineer/Lead Software Engineer you will play a crucial role in designing developing and maintaining our data infrastructure. You will be responsible for ensuring the availability reliability and accuracy of data while creating visually appealing and insightful reports and dashboards.
Specifically your role will involve:
- Collaborating with crossfunctional teams to understand data requirements and translate them into efficient data models and visualizations
- Designing and implementing robust ETL pipelines using PySpark for efficient data processing and utilizing Pytest for comprehensive unit and integration testing to ensure data quality and reliability
- Building and optimizing data models to support complex analytical queries and reporting needs
- Implementing data governance and data quality best practices to ensure data integrity and accuracy
- Monitoring and troubleshooting data issues ensuring timely resolution and proactive identification of potential bottlenecks
- Staying up to date with the latest features tools and best practices to continuously improve data analytics capabilities
- Integrating AI and machine learning techniques to enhance data processing and analysis including developing predictive models and automating data workflows
Qualifications :
- Degree in Software Engineering Information Technology or equivalent professional qualification
- Proficiency in Python Programming
- Tenacious with a passion to get the job done
- Proficiency in Data Engineering Tools: Experience with Argo Workflow for orchestrating complex data pipelines Kafka for realtime data streaming and Change Data Capture (CDC) techniques for efficient data replication and synchronization
- Indepth understanding of relational databases data warehousing concepts and SQL
- Familiarity with data modeling data integration and data governance principles
- Analytical and Reporting skills (Power BI Apache Superset) would be a plus
- Strong analytical and problemsolving skills with the ability to translate complex data into actionable insights
- Excellent communication and collaboration skills to work effectively with crossfunctional teams
- Experience with AI and machine learning frameworks and techniques
- Previous experience or knowledge working with sustainability data such as GHG emissions and ESG metrics would be an added advantage.
Additional Information :
Interviews and selections are being made continuously. If you are interested apply as soon as possible.
As a step in our recruitment process all final candidates will undergo a background check to get us an understanding of our future employees.
We respectfully decline all offers of recruitment and/or advertising assistance.
We embrace flexibility and hybrid work opportunities to support diverse needs and lifestyles while also valuing inclusive workplace experiences. By fostering a sense of community we drive innovation strengthen connections and nurture belonging. Our commitment ensures you can work in a way that suits you best while also engaging with colleagues to share ideas and build meaningful relationships.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
