Data Product & Platform Operations Engineer
Justergroupab
| Company | Justergroupab |
| Category | Engineering |
| Location | — |
| Remote | — |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 22 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (teamtailor) |
Description
About Justera Group Justera Group AB is a leading Swedish IT consulting firm with great experience specializing in building high-performing technology teams and delivering end-to-end IT solutions. Led by dynamic female executives, Justera Group focuses on helping businesses harness the power of digital technologies to continuously evolve in today’s rapidly changing economy. The company has deep expertise in IT consultancy, software development, and recruitment services, providing clients with purpose-driven, well-trained consultants who consistently deliver efficient and effective results. Justera Group manages the entire talent lifecycle, from hiring to ongoing management, ensuring the right fit for each project on time and within budget. With their strong commitment to quality, collaboration, and client success, Justera Group is a trusted partner for technology innovation across Sweden. About the Role: We are seeking an experienced Data Product & Platform Operations Engineer to support the development and operation of a modern enterprise data platform built on Microsoft Fabric. This role focuses on enabling scalable, governed, and self-service data products while strengthening platform operations, observability, governance, and FinOps capabilities. The successful candidate will work across data platform engineering and business intelligence initiatives, contributing to the design, implementation, and operational excellence of enterprise data products. This is a hands-on engineering role suited for someone who enjoys building reusable solutions, improving platform reliability, and collaborating with both technical and business stakeholders. Key Responsibilities: Design, build, and operate end-to-end data products on Microsoft Fabric , from data ingestion through Bronze, Silver, and Gold layers to consumption-ready datasets. Develop reusable engineering assets, including parameterized pipelines, metadata-driven ingestion frameworks, notebook libraries, and standardized delivery patterns. Implement data contracts, metadata standards, ownership models, lifecycle management, and governance controls. Build and enhance domain-specific data products while supporting enterprise reporting and analytics initiatives. Implement and maintain data cataloging, lineage, classification, ownership, and data quality using Microsoft Purview and/or Fabric-native capabilities. Define and automate data quality checks, validation rules, certification processes, and operational governance controls. Develop operational dashboards for platform health, pipeline performance, refresh monitoring, usage analytics, incidents, and cost visibility. Establish and maintain SLAs, SLOs, incident management processes, runbooks, and continuous service improvement practices. Drive FinOps activities, including capacity monitoring, cost allocation, showback reporting, anomaly detection, and optimization recommendations. Support onboarding of domain teams by promoting platform standards, best practices, and reusable delivery patterns. Create clear technical documentation and contribute to knowledge sharing to reduce operational dependencies. Requirements: Strong hands-on experience in Data Engineering using PySpark/Spark, SQL, Python, and pipeline orchestration. Practical experience with Microsoft Fabric, or strong experience with Azure Databricks or Azure Synapse Analytics with the ability to transition to Fabric. Experience working with Lakehouse architecture, notebooks, pipelines, and OneLake or equivalent data platform concepts. Strong understanding of incremental loading strategies, CDC, and event-driven data ingestion. Experience building reusable frameworks, templates, and scalable data products rather than one-off implementations. Hands-on experience implementing data governance, including metadata management, cataloging, lineage, documentation, and operationa
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