Data Engineer

Develop, optimize, and operate resilient data pipelines for ingestion, replication/CDC, and transformation across cloud and on-Prem sources, leveraging Microsoft Fabric and/or Azure data services to meet defined SLAs (batch and near real-time). ‑prem sources, leveraging Microsoft Fabric and/or Azure data services to meet defined SLAs (batch and near real-time) 

Implement modern lakehouse/warehouse patterns using Medallion architecture including data quality checks, lineage/metadata, and standardized reusable data products. 

Design, test, and implement dimensional data models (star schemas, conformed dimensions, fact tables, aggregates) to support enterprise reporting, self-service analytics, and governed metric definitions. 

SQL engineering and performance optimization across relational platforms (e.g., SQL Server/Azure SQL/Fabric Warehouse SQL), including query tuning, troubleshooting production issues, and improving data structures for reliability and scale.  

Enable analytics and reporting by publishing curated datasets and semantic models, supporting Power BI development best practices (performance, incremental refresh patterns, RLS/OLS, reusable measures) and contributing to migration away from legacy reporting (e.g., SSRS) where applicable 

Ingest and curate semi-structured and unstructured data (JSON, APIs, logs, files), managing schema evolution, validation, and scalable storage formats. 

Collaborate on enterprise data governance: data definitions, data contracts, documentation, cataloging, and stewardship practices to ensure consistency and trusted data across domains 

Be highly responsive to critical production issues providing timely and effective solutions. 

Participate in code reviews both as a reviewer and as a reviewee, in a respectful way that facilitates skill building for all team members. 

Engage in all aspects of the Agile process, proactively contributing to improvements in the processes to minimize rework/waste and increase quality and velocity. 

Keep abreast of software industry best practices, processes, and technologies.  

Communication – Able to clearly and articulately present information in both spoken and written word. 

Collaboration – Develops positive relationships with others to build consensus, morale and commitment to goals and objectives. 

Innovation – Displays the ability to think outside of the box to develop creative and new solutions that meets current and future needs. 

Flexibility – Easily adapts to changing environment and resources. 

Productivity – Strives to consistently achieve excellence in all tasks and goals. 

Accountability – Takes personal ownership and responsibility for the quality and timeliness of work commitments and decisions. 

Strong experience in data engineering, ETL/ELT, and data warehousing, including dimensional modeling and delivering curated data marts/data products. 

Advanced T‑SQL (Transact‑SQL) skills for development, troubleshooting, and maintenance of legacy ETL processes and data pipelines (e.g., SSIS/SQL Server–based workloads). 

Experience with Microsoft cloud data platforms, with preference for Microsoft Fabric and/or Azure services such as OneLake, Lakehouse/Warehouse, Data Pipelines, Dataflows Gen2, Notebooks/Spark, Mirroring 

Experience enabling Power BI at scale, including semantic model fundamentals (measures, relationships, performance patterns) and governance practices (certification, shared datasets, workspace standards). SSRS experience. Ability to think creatively. 

Post-secondary education in Computer Science or related discipline 

3+ years development and maintenance of Data Warehouses and ETL processes