DescriptionAs of November 1, 2025, Sunoco LP has successfully completed its acquisition of Parkland Corporation. For more information, please visit ;br>
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 into clear technical designs and collaborate effectively with technical and non-technical partners.
- Strong troubleshooting, documentation, communication, and ownership skills.
Preferred Qualifications- Direct Azure Databricks experience and the ability to translate prior Fabric or Synapse data engineering patterns into Databricks implementations.
- Databricks experience with Unity Catalog, Workflows, Asset Bundles, Delta Live Tables or Lakeflow Declarative Pipelines, Auto Loader, and performance tuning.
- Microsoft Fabric or Azure Synapse Analytics experience with lakehouse or warehouse development, notebooks, Spark, pipelines, orchestration, and deployment practices.
- Experience with GitHub Actions, YAML, automated testing, deployment pipelines, or infrastructure-as-code; deep DevOps platform-engineering expertise is not required.
- Experience building reusable data engineering frameworks, templates, libraries, or common ingestion patterns.
- Knowledge of Microsoft Fabric, Power BI, semantic models, and downstream analytics consumption as the presentation layer for curated Databricks data products, while remaining primarily focused on data engineering.
- Working knowledge of data mesh, domain-oriented data products, and federated governance.
- Experience with Azure services such as ADLS Gen2, Azure Data Factory, Key Vault, Entra ID, Managed Identities, and RBAC.
- Experience with ServiceNow and ITIL-aligned incident, problem, and change-management practices.
- Experience in energy, midstream, or another FERC- or SOX-regulated industry.
Humble. Hungry. Smart. Does this sound like you?Do others describe you as being a down-to-earth achiever? Someone who thinks outside the box and always strives to do more than what is required? Someone who sees the bigger picture? You sound brilliant to work with!
We Want You To Shine:We are committed to providing equal opportunities to all applicants. If you require accommodation due to a disability, you will have an opportunity to notify us when scheduling your interview.
Belonging Matters. Because You Do:We are an equal opportunity employer and encourage applications from all qualified individuals. Our ability to work as one team across Canada, the United States, and the Caribbean is foundational to our success. We show up as our authentic selves each day and create space for one another's unique contributions.
We respect the diverse cultures, traditions, and perspectives of Indigenous Peoples and seek to achieve equitable partnerships and opportunities with Indigenous communities.
The Fine Print:Candidates must be legally eligible to work in the country in which they applied. Regrettably, we are unable to sponsor employment visas at this time.
Final candidates will be required to undergo a confidential pre-employment background check, including but not limited to educational, criminal, credit, drug and alcohol, and/or fitness for duty testing.
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
