Senior Business Intelligence Engineer
OEC · PL ·
- Seniority
- Senior
- Category
- Data analytics
- Experience
- 6+ years
OEC · PL ·
Team
We are a team focused on creating tools and solutions that leverage the massive amount of data OEC processes each day. We build end-to-end analytics systems spanning data ingestion, transformation, warehousing, and reporting — all on the Microsoft Fabric platform. We are also actively building AI-powered agents and assistants that help clients unlock insights from their data. If Microsoft Fabric, Data Engineering, and Power BI are the concepts that make your heart beat faster - we will have a lot in common.
Key Responsibilities
Design and implement end-to-end data engineering pipelines using Microsoft Fabric (Data Factory, Lakehouse, Notebooks, Warehouse).
Build and maintain Delta Lake–based data models stored in OneLake, ensuring data quality, ACID compliance, and schema governance.
Develop and optimize T-SQL queries, stored procedures, and SQL analytics endpoints against Fabric Data Warehouse.
Implement ETL/ELT processes using Fabric Pipelines, Dataflows Gen2, and PySpark Notebooks.
Design and develop Power BI semantic models, interactive dashboards, and reports.
Contribute to the development of AI-powered analytics agents embedded in OEC products to support clients in data analysis.
Own design, development, and maintenance of ongoing metrics, reports, analyses, and dashboards driving key business decisions.
Provide technical guidance and mentoring to mid and junior engineers.
Create and maintain documentation of processes, data models, and procedures.
Experience, Skills and Key Competencies
Engineer's, Bachelor's, or Master's degree in Computer Science, Software Engineering, Mathematics, or a related field.
At least 6 years of experience in Business Intelligence, Data Engineering, and Data Warehouse development.
Hands-on experience with Microsoft Fabric (Lakehouse, Data Factory Pipelines, Dataflows Gen2, Fabric Notebooks, Data Warehouse, Power BI) or with MS Azure platform (Azure Data Factory, Azure SQL, Azure Blob Storage, Entra ID).
Strong T-SQL skills and solid understanding of BI/DWH concepts and Data Modelling (star schema, dimensional modelling).
Experience building ETL/ELT pipelines and working with Delta Lake / Parquet format in OneLake.
Hands-on experience with PySpark and Python for data transformation and processing in Fabric Notebooks.
Work experience with Power BI and DAX/M/Tabular modelling.
Experience with GitHub for version control and CI/CD.
Experience with Agile development methodologies.
Proactive, self-organizing, and solutions-oriented mindset with strong attention to detail.
Advanced English language skills: speaking and writing.
Nice to Have
Familiarity with Data Science and Machine Learning concepts — understanding of model training, evaluation, feature engineering, and deployment in an analytics context.
Experience integrating AI/ML capabilities into BI or data products (e.g. predictive analytics, intelligent assistants, LLM-based features).
Experience with MLOps practices and tooling — model versioning, experiment tracking, automated retraining pipelines, and model monitoring in production (e.g. MLflow, Azure ML, or similar).