Senior Business Intelligence and Data Engineer

We are looking for a Modern BI / Data Warehouse Developer who can bridge traditional BI engineering (T-SQL, ETL, SSIS-nice to have) with modern cloud analytics patterns, including building scalable data pipelines into Microsoft Fabric and creating transformations using notebooks (Python/Pandas) and related tooling.

This role focuses on data ingestion, modeling, transformations, and semantic layer readiness. While the role will not be responsible for building production reports, the ideal candidate understands reporting needs well enough to design data models and semantic models that support analytics and self-service BI., + Design and implement data ingestion pipelines to move data from source systems (SQL, files, APIs, SaaS apps) into Microsoft Fabric (e.g., Lakehouse/Warehouse).

• Create and maintain pipelines using Azure Data Factory (ADF) and/or Fabric-native orchestration patterns as appropriate.

• Build transformation logic using notebooks and modern approaches (Python, Pandas, Spark where applicable).

• Apply best practices for:

• data quality checks & validations

• reproducibility (parameterization, modular notebooks, version control)

• performance optimization (partitioning, pushdown, caching strategies where relevant)

• Design and maintain enterprise data warehouse models

• Understand how to prepare data for semantic models and analytics consumption:

• Collaborate with report developers/analysts by ensuring data models align with real BI usage patterns.

• Work closely with stakeholders (analysts, app teams, data owners) to translate requirements into scalable pipelines and models.

• Participate in code reviews, documentation, and operational handoffs.

• Help establish standards for naming, versioning, environments, and deployment patterns.

• Strong hands-on experience with T-SQL and relational data modeling.

• Proven experience building ETL/ELT pipelines and supporting production data workflows.

• Experience with Azure Data Factory (ADF) or comparable orchestration tools.

• Experience building transformations using notebooks, including Python and Pandas (and/or Spark-based transformations as needed).

• Strong understanding of:

• modern data warehousing

• dimensional modeling (facts/dimensions, SCDs, conformed dimensions)

• performance fundamentals (indexes, partitioning concepts, query tuning as applicable)

• Working knowledge of reporting concepts (requirements, visual performance considerations, data shaping), even if not building reports.

• Nice to have skills:

• TensorFlow, PyTorch, Hugging Face

• SSIS experience (nice-to-have, not required).

• Experience with Microsoft Fabric components (Lakehouse, Warehouse, pipelines, notebooks, shortcuts, etc.).

• Familiarity with semantic modeling platforms and patterns (e.g., Power BI semantic models/tabular concepts).

• Exposure to data governance, cataloging, and lineage practices.

• Experience with CI/CD for data assets (Git integration, environment promotion)., + 3+ years of professional experience in BI, data engineering, or data warehouse development in an enterprise environment.

• 2+ years of hands-on experience with T-SQL, including:

• complex joins, window functions, CTEs

• query optimization and performance tuning

• building and maintaining transformation logic in SQL

• 2+ years of experience designing and implementing ETL/ELT pipelines.

• 1+ years of experience building data pipelines using Azure Data Factory (ADF) or a comparable orchestration tool.

• 3+ years of experience with modern data warehousing principles, including:

• layered architectures (raw, curated, consumption)

• ELT patterns batch and incremental loading strategies

• 3+ years of hands-on dimensional data modeling experience, including:

• star and snowflake schemas

• fact and dimension table design

• surrogate keys and SCD (Type 1/2) patterns

• 1+ years of experience developing data transformations using notebooks.

• Working knowledge of reporting and analytics tools concepts (e.g., how analysts and business users consume data), even if not responsible for building reports directly.

• Professional communications skills, both verbal and written. Good team player.

• Manage personal workload and work under tight timeframes.

• Must be able to work independently with minimal supervision.

• Bachelor’s degree in Computer Science, Engineering, or a related field preferred.

PHYSICAL DEMANDS:

• Occasional: bending, kneeling, squatting, standing, walking, reaching, overhead reaching, and fine motor skills