Full proficiency in Microsoft SQL Server and T-SQL: stored procedures, views, and user-defined functions (mandatory).
Full proficiency in Power BI (mandatory).
Experience in creating reports using SQL Server Reporting Services (SSRS). If the candidate lacks this skill but excels in the previous two, we can provide training on SSRS.
Design, build, and maintain scalable data pipelines and workflows using Microsoft Fabric, including Data Factory, Lakehouse, and Synapse Pipelines.
Use Apache Spark in Microsoft Fabric Notebooks for large-scale data processing, cleansing, and transformation tasks.
Develop efficient SQL-based solutions for data modeling, data warehousing, and analytics layers.
Leverage Python and PySpark to automate data flows, integrate sources, and apply advanced data logic.
Collaborate with analysts, engineers, and stakeholders to deliver clean, trustworthy datasets to reporting and ML pipelines.
Assist in establishing data quality, data lineage, and governance processes across the data stack.
Act as a subject matter expert on data workflows within the Microsoft ecosystem, helping to guide best practices across teams.
Requirements
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
Hands-on experience with Microsoft Fabric components including Spark Notebooks, Data Factory, and Synapse.
Strong understanding of Apache Spark (especially via PySpark) for distributed data processing.
Proficiency in SQL for data manipulation and optimization.
Solid Python skills for scripting, automation, and transformation logic.
Experience with cloud-native data solutions—preferably on Microsoft Azure.
Understanding of data warehouse design, dimensional modeling, and Lakehouse patterns.
Familiarity with CI/CD and version control tools (e.g., Git, Azure DevOps).
Comfortable working in agile, iterative data development cycles.
Excellent communication and stakeholder collaboration skills.
Nice to Have:
Familiarity with OneLake architecture and Delta Lake implementation in Fabric.
Knowledge of Power BI data modeling and how backend data impacts reports.
Experience with streaming data ingestion (e.g., Azure Event Hubs, Kafka, Fabric Real-Time Analytics).
Exposure to notebook-based development workflows in Jupyter or Databricks.
Awareness of data privacy, security best practices, and compliance (e.g., GDPR, DLP tools).
Previous experience with other Spark platforms like Databricks or HDInsight is a plus.
Tech Stack
Apache
Azure
Cloud
Kafka
MS SQL Server
PySpark
Python
Spark
SQL
Benefits
Salary 4750
5000 EUR gross/month.
Work within a dynamic international team of experts Excellent opportunity for personal and professional development .
Flexible work model and the freedom to choose the tools that suit you best – Mac or Window.
Ability to work with modern technologies.
Extensive catalogue of educational programs, the possibility of training and certification at the expense of the company.