Data Analytics Engineer

Function

We’re looking for a Data Engineer to join our client’s innovative digital transformation journey. This is an exciting opportunity to contribute to a large-scale modernization program where data and technology play a central role in driving smarter operations, sustainable infrastructure, and data-driven decision-making. You will join a collaborative, cloud-first agile environment where business stakeholders, analysts, and IT experts work closely together to deliver scalable and future-proof data solutions.

The Role

As a Data Engineer, you will work from business challenges and opportunities rather than predefined technical tickets. Together with analysts and stakeholders, you will identify the right data insights needed to support strategic and operational decisions. You will take ownership of data products end-to-end — from source integration and modeling to delivery and governance — ensuring solutions are reusable, scalable, and aligned with architectural standards.

You will also contribute to shaping the organization’s data product architecture by defining standards, templates, and best practices that support consistent delivery across teams. In this role, you are expected to combine technical expertise with strong business understanding and a product-oriented mindset.

Key Responsibilities

• Design, develop, and maintain scalable data products for multiple business consumers
• Build and optimize data pipelines, transformations, and dimensional data models
• Translate business requirements into robust and reusable data solutions
• Contribute to the evolution of the data platform and data product architecture
• Define and promote standards related to governance, quality, security, and lifecycle management
• Collaborate closely with Business Information Analysts, technical teams, and business stakeholders
• Deliver data models and datasets for reporting and analytics platforms such as Power BI
• Support AI-driven delivery approaches, including automated testing, documentation, and model generation
• Ensure data products are reliable, well-documented, understandable, and discoverable
• Work within an agile SAFe environment and actively contribute to continuous improvement initiatives

Ideal Candidate

• Strong experience with SQL and hands-on knowledge of Python and/or PySpark
• Proven expertise in data modeling, including dimensional modeling and Kimball methodologies
• Experience working with modern cloud-based data ecosystems such as Azure Databricks, Azure Data Factory, Microsoft Fabric, or similar technologies
• Knowledge of DBT, CI/CD pipelines, version control (Git), and software engineering best practices is considered a strong advantage
• Ability to bridge the gap between business and technology through strong analytical and communication skills
• Experience contributing to data platform architecture, governance frameworks, or data product thinking
• Comfortable working in agile environments with shifting priorities and cross-functional collaboration
• Curious, proactive, and driven by delivering business value through high-quality data solutions
• Experience integrating data from complex enterprise environments such as ERP or asset management systems is a plus