Job Description
The company and our mission: Zartis is a global AI transformation and technology consulting partner where talented engineers and technologists work on cutting edge innovation. We partner with ambitious organizations to design, build, and scale technology solutions that deliver real impact. Our teams bring deep expertise in AI driven platforms, secure API architectures, and cloud native engineering. You will work on meaningful projects that accelerate the adoption of advanced technologies, from strategy and discovery through to full product delivery, helping turn complex challenges into measurable outcomes. With engineering hubs across EMEA and LATAM, and long term partnerships in financial services, healthcare and life sciences, and energy and climate, we offer opportunities to work on projects that truly matter. Here, you will not just build technology, you will drive business impact and grow your career alongside industry leaders. We are looking for a Senior Data Engineer to work on a project in the industrial engineering services industry. The project: We are talented people that come from a variety of backgrounds. We’re committed to building an inclusive culture based on trust and innovation. You will be part of a distributed team developing new technologies to solve real business problems. We are looking for a Senior Data Engineer to join our client small data team, working alongside one existing Power Platform/data engineer as a peer. The role combines Power Platform development (Power Apps, Power Automate, Power BI) with hands-on data engineering using Python, SQL, Azure Data Factory, and Microsoft Fabric. The immediate priority is data ingestion: helping migrate and ingest data from a variety of sources into a Fabric medallion architecture (Bronze/Silver/Gold). Once this priority workload is established, focus will shift to broader work including CI/CD pipeline hardening, development standards, and best practice across the team's Power Platform and Fabric estate. This is a hands-on technical role, where you'll be working day-to-day alongside the existing engineer, sharing knowledge, and contributing equally to delivery. What you will do: Design, build, and maintain pipelines to ingest and migrate data from a variety of sources (on-prem databases, APIs, flat files, line-of-business systems) into Microsoft Fabric. Implement and maintain Fabric medallion architecture (Bronze/Silver/Gold layers), structuring transformation logic for data quality and consistency. Write Python (e.g. PySpark, notebooks) and SQL for data transformation, cleansing, and modelling within Fabric Lakehouses and Warehouses. Build and orchestrate pipelines using Azure Data Factory and/or Fabric Data Factory. Develop and maintain Power Apps (canvas and model-driven) for operational engineering use cases. Build Power Automate flows that integrate with Azure services and Fabric data Develop Power BI reports and dashboards consuming curated Fabric (Gold layer) data. Maintain and extend Dataverse tables, relationships, and security Models. Contribute to hardening CI/CD pipelines for both Power Platform solutions and Fabric/data engineering code, using Azure DevOps. Help establish and document development standards, naming conventions, and code review practices. Support governance activities including environment strategy, DLP policies, and Fabric workspace/capacity management. Liaise with engineering stakeholders to understand requirements for data, automation, and reporting needs. Provide ongoing support and troubleshooting for existing pipelines, flows, and apps. What you will bring: Hands-on development experience across Power Apps, Power Automate, and Power BI. Strong working proficiency in Python and SQL for data transformation and pipeline development. Practical experience with Microsoft Fabric, including medallion architecture (Bronze/Silver/Gold), Lakehouses, and Dataflows Gen2. Experience with Azure Data Factory (or Fabric Data Factory) for orchestrating data ingestion and transformation pipelines. Experience migrating or ingesting data from diverse sources (databases, APIs, files, legacy systems) into a modern data platform. Solid understanding of Dataverse, including table design, security roles, and relationships. Experience working in an engineering, manufacturing, or industrial sector. Comfortable working collaboratively as part of a small team, sharing knowledge and reviewing peers' work. Familiarity with Azure DevOps for source control and release management. Nice to have: Microsoft certifications (e.g. PL-400, PL-300, DP-600 or DP-700). Experience with PySpark notebooks in Microsoft Fabric. Knowledge of CI/CD pipelines for Power Platform and data engineering solutions. Exposure to Copilot Studio or AI Builder. Experience working with engineering, manufacturing or industrial data. Understanding of IoT or sensor data integration. What we offer: 100% Remote Work WFH allowance: Monthly payment as financial support for remo
