Specialist, BI Developer

As of November 1, 2025, Sunoco LP has successfully completed its acquisition of Parkland Corporation.

For more information, please visit www.sunocolp.com. Sunoco LP is a leading energy infrastructure and fuel distribution master limited partnership operating across 32 countries and territories in North America, the Greater Caribbean, and Europe. The Partnership’s midstream operations include an extensive network of approximately 14,000 miles of pipeline and over 160 terminals. This critical infrastructure complements the Partnership’s fuel distribution operations, which distribute over 15 billion gallons annually to approximately 11,000 Sunoco and partner-branded retail locations, as well as independent dealers and commercial customers. At Sunoco, we take great pride in what we do and wholeheartedly believe our employees drive success for our company and our customers. We are always looking for the best and brightest talent and are committed to making your job a challenging and rewarding experience. Competitive Benefits. Meaningful Extras. Unmatched Value.

A place where you can take your career in the direction you want to grow and go The Opportunity:

Join the Enterprise Business Intelligence team as a BI Developer focused primarily on data engineering within our Azure Databricks platform. This role designs, builds, tests, and supports trusted data products and pipelines in Databricks, including ingestion, transformation, orchestration, data quality, and production support. Microsoft Fabric serves primarily as a presentation and downstream consumption layer for the data products developed in Databricks. The ideal candidate brings strong data engineering experience from Databricks or a comparable Microsoft platform such as Fabric or Azure Synapse Analytics and can apply that experience within our Databricks environment. A strong background in Azure infrastructure and networking is a big plus, but not a requirement.

Responsibilities:

Design, build, and maintain scalable data pipelines and curated data products in Azure Databricks. Develop data transformations using SQL and Python, with an emphasis on reliability, maintainability, performance, and reuse. Implement medallion-style data architectures and dimensional or analytical data models that support reporting, analytics, and downstream applications. Use Databricks capabilities such as Delta Lake, Unity Catalog, Workflows, notebooks, Auto Loader, and Delta Live Tables or Lakeflow Declarative Pipelines as appropriate to the solution. Partner with business analysts, BI developers, source-system teams, and data owners to translate business requirements into well-defined, governed data products. Build automated data-quality checks, monitoring, alerting, reconciliation, and operational support processes for production pipelines. Work within GitHub-based delivery practices, including source control, branching, pull requests, code review, CI/CD, and environment promotion. Contribute to reusable engineering standards, templates, documentation, and development patterns without serving as the primary DevOps platform owner. Apply security and governance practices across data access, sensitive data, lineage, metadata, and cataloging, with particular emphasis on Unity Catalog and alignment with broader Microsoft Purview capabilities. Troubleshoot pipeline failures, data defects, and performance issues; perform root-cause analysis and coordinate fixes through established incident and change processes. Support production changes, incidents, requests, and problem management in ServiceNow using appropriate testing, approval, communication, and rollback controls.

Education:

A bachelors degree in MIS, Computer Science, or equivalent degree

Requirements:

3+ years of experience developing production data pipelines, data transformations, or analytical data products. Strong hands-on data engineering experience with Azure Databricks, Microsoft Fabric, or Azure Synapse Analytics. Experience gained in Fabric or Synapse is considered qualifying when it includes production pipelines, lakehouse or warehouse development, Spark or notebook-based engineering, orchestration, and operational support. Strong SQL skills and practical Python or PySpark experience for data ingestion, transformation, testing, and automation. Experience with lakehouse architecture, Delta tables, layered data design, data modeling, and performance optimization. Experience orchestrating and monitoring batch or near-real-time data pipelines, including dependency management, retries, and failure handling. Working knowledge of Git and GitHub, including branches, pull requests, code review, and basic CI/CD concepts. Experience implementing data-quality checks, reconciliation, logging, monitoring, and production support practices. Understanding of data security, access controls, governance, lineage, and metadata management. Ability to translate business requirements i