As part of the Core Engineering Services team, we are seeking an Azure Data Engineer to support the design, development, and maintenance of scalable data pipelines and cloud-based data solutions. We are looking for a hands‑on specialist focused on building, optimizing, and supporting data workflows within our Azure and Databricks environment. Essential Functions/Core Responsibilities Pipeline Development: Build and maintain robust data pipelines for ingesting, transforming, and loading data into the Azure data lake. Workflow Management: Develop and support orchestration and workflow monitoring solutions to ensure reliable data delivery. Performance Tuning: Write and optimize complex SQL queries; improve data performance via advanced query tuning and indexing. API Development: Develop backend data APIs and support API management configurations for seamless data exchange. External Integration: Integrate with external systems and REST APIs to facilitate diverse data flows. Streaming & Events: Manage the ingestion of streaming or event‑based data (e.g., Event Hubs) into the ecosystem. Infrastructure, DevOps & Quality Infrastructure as Code: Implement and maintain Azure resources using YAML‑based configurations. CI/CD & Versioning: Contribute to CI/CD pipelines using Azure DevOps and maintain strict version control, logging, and monitoring. Data Governance: Support rigorous data quality checks, validation processes, and adhere to engineering best practices through code reviews. Candidate Profile Education: Bachelor’s degree in Computer Science, Information Systems, or a related field. Experience: 3+ years of hands‑on experience in data engineering roles. Technical Core Language Mastery: Proficiency in Python (processing scripts/utilities) and SQL (transformation/analysis). Cloud Ecosystem: Practical experience with Azure and Databricks; familiarity with Lakehouse architectures. Data Modeling: Strong understanding of relational data models (Star/Snowflake, Kimball) and ETL/ELT concepts. Big Data Tools: Experience working with Spark or similar big data technologies. Professional Experience Technical Problem‑Solver: Strong troubleshooting skills related to pipelines, jobs, and cloud components. Collaborative Engineer: Experience working in Agile environments (Jira/GitHub), partnering with technical teams to translate requirements into solutions. Self‑Directed: Ability to work independently with minimal oversight, meeting deadlines across multiple simultaneous projects. Technical Stack Summary Languages: Python, SQL Data/Messaging: Spark, Event Hubs, RESTful APIs Architecture: Lakehouse, Star/Snowflake Schema #J-18808-Ljbffr