diconium
Fabric Data Engineer (All genders)
- Compensation
- Not disclosed
- Location
- Bucharest
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 5+ years of hands-on experience in Data Engineering, including the design and delivery of large-scale data pipelines and cloud data platforms.
- Strong practical experience with Microsoft Fabric, including Lakehouse, OneLake, Data Factory pipelines, notebooks, Apache Spark, and Fabric Warehouse.
- Advanced programming skills in Python and SQL, with hands-on experience in PySpark or Spark SQL for distributed data processing.
- Strong background in data integration, ETL/ELT development, data modeling, data architecture, and analytics-oriented solution design.
- Experience designing reliable batch-processing solutions and integrating data from multiple enterprise source systems.
- Understanding of Delta Lake concepts, partitioning, schema evolution, incremental loading, and performance optimization.
- Experience implementing security, access control, data-quality checks, monitoring, logging, testing, and production support for data solutions.
- Experience with Git-based development and CI/CD practices using Azure DevOps, GitHub Actions, or comparable tooling.
- Ability to communicate technical decisions clearly, work effectively with cross-functional teams, and take ownership from design through production.
Nice to have
- Experience with additional Fabric capabilities such as Dataflow Gen2, Eventstream, Real-Time Intelligence, Direct Lake, semantic models, or Power BI.
- Knowledge of Microsoft Purview, Microsoft Entra ID, workspace governance, sensitivity labels, lineage, and enterprise data-governance practices.
- Experience with Azure services that commonly complement Fabric, such as Azure Data Lake Storage, Azure SQL, Azure Functions, Event Hubs, Key Vault, or private networking.
- Exposure to Infrastructure-as-Code and deployment automation using Terraform, Bicep, REST APIs, or Fabric deployment pipelines.
- Knowledge of streaming technologies such as Kafka or Azure Event Hubs.
- Experience migrating solutions from Azure Data Factory, Azure Synapse Analytics, Databricks, or other cloud data platforms to Microsoft Fabric.
- Relevant Microsoft certifications, such as Fabric Data Engineer Associate, or equivalent practical expertise.
- Experience working in Agile delivery environments and consulting or customer-facing projects.
Full description
Join our global team of experts
At Diconium, you will work on projects that connect software, data, AI, and human expertise to create digital products, services, and operating models that deliver measurable business impact. Together with 2,500 experts across our international teams, you will help build, run, and scale intelligence across the full value chain.
In everything we do, we prioritize people and genuine human connections, ensuring a supportive and inclusive work environment. Our hybrid workplace also provides a high degree of flexibility.
WHAT YOU CAN EXPECT
- Design, build, and operate scalable batch and near-real-time data pipelines in Microsoft Fabric, using Data Factory pipelines, Dataflow Gen2, notebooks, and Spark job definitions.
- Create and maintain Lakehouse and Warehouse solutions in OneLake, applying robust medallion, dimensional, and data-product design patterns.
- Develop data ingestion, cleansing, transformation, and integration logic using Python, PySpark, Spark SQL, T-SQL, and Power Query where appropriate.
- Integrate structured, semi-structured, and unstructured data from cloud, on-premises, SaaS, API, file, and streaming sources.
- Optimize data pipelines and analytical workloads for performance, reliability, maintainability, and efficient Fabric capacity consumption.
- Implement engineering standards for data quality, observability, metadata, lineage, security, testing, exception handling, and operational support.
- Work closely with Data Scientists, BI Developers, Analysts, Architects, and business stakeholders to translate data requirements into reusable, analytics-ready solutions.
- Contribute to CI/CD, source control, automated deployment, environment management, and release practices for Fabric workspaces and data products.
- Evaluate new Microsoft Fabric capabilities and recommend pragmatic improvements to the data platform and delivery approach.
- Share expertise with team members and maintain clear technical documentation, runbooks, standards, and best practices.
WHAT YOU BRING ALONGMust haves
- 5+ years of hands-on experience in Data Engineering, including the design and delivery of large-scale data pipelines and cloud data platforms.
- Strong practical experience with Microsoft Fabric, including Lakehouse, OneLake, Data Factory pipelines, notebooks, Apache Spark, and Fabric Warehouse.
- Advanced programming skills in Python and SQL, with hands-on experience in PySpark or Spark SQL for distributed data processing.
- Strong background in data integration, ETL/ELT development, data modeling, data architecture, and analytics-oriented solution design.
- Experience designing reliable batch-processing solutions and integrating data from multiple enterprise source systems.