Data Engineer

We are looking for a Data Engineer to join a team focused on building reliable, scalable data solutions. In this role, you will create and enhance cloud-based data pipelines, organize data for analytics, and help ensure that business teams have access to trusted information. This position also partners closely with technical and non-technical stakeholders to turn reporting and data needs into practical engineering outcomes., * Create and support scalable data ingestion and transformation workflows using Azure Data Factory, Databricks, and PySpark.

• Connect and consolidate data from enterprise platforms, operational databases, telematics feeds, APIs, and other internal or external sources.

• Structure and manage data within Azure Data Lake and lakehouse environments to support performance, accessibility, and long-term maintainability.

• Design curated datasets, data models, and schemas that improve usability for analytics, business intelligence, and downstream reporting.

• Apply governance and lineage practices through Unity Catalog while promoting strong data quality, consistency, and security standards.

• Work with business stakeholders and cross-functional teams to gather requirements, define technical specifications, and deliver data solutions aligned with operational needs.

• Improve pipeline stability and efficiency by troubleshooting failures, resolving performance issues, and refining storage and query strategies.

• Support Power BI reporting by preparing datasets, assisting with model improvements, and helping maintain reporting standards and governance practices.

• Use GitHub-based development practices for version control, peer review, CI/CD, and disciplined deployment processes.

• Mentor less-experienced engineers and contribute to a collaborative environment focused on continuous improvement and dependable delivery.

Requirements * Hands-on experience with Azure Data Factory, Azure Databricks, and Azure Data Lake in a data engineering environment.

• Strong programming ability in Python and PySpark for large-scale data processing and transformation.

• Proficiency in SQL, including writing and optimizing queries for analytics and data integration workloads.

• Experience building and maintaining ETL or ELT pipelines that combine data from multiple structured and semi-structured sources.

• Familiarity with data modeling concepts, curated dataset design, and preparation of data for BI or analytics consumption.

• Understanding of data governance, lineage, and security practices within modern cloud data platforms.

• Experience using GitHub or similar tools for source control, code review, and deployment automation.

• Ability to communicate effectively with business partners and translate functional needs into scalable technical solutions. Technology Doesn't Change the World, People Do.®, All applicants applying for U.S. job openings must be legally authorized to work in the United States. Benefits are available to contract/temporary professionals, including medical, vision, dental, and life and disability insurance. Hired contract/temporary professionals are also eligible to enroll in our company 401(k) plan. Visit roberthalf.gobenefits.net for more information.

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