<p>The Data Engineer role focuses on designing, building, and optimizing scalable data solutions that support diverse business needs. This position requires the ability to work independently while collaborating effectively in a fast-paced, agile environment. The individual in this role partners with cross-functional teams to gather data requirements, recommend enhancements to existing data pipelines and architectures, and ensure the reliability, performance, and efficiency of data processes.</p><p>Responsibilities</p><ul><li>Support the team’s adoption and continued evolution of the Databricks platform, leveraging features such as Delta Live Tables, workflows, and related tooling</li><li>Design, develop, and maintain data pipelines that extract data from relational sources, load it into a data lake, transform it as needed, and publish it to a Databricks-based lakehouse environment</li><li>Optimize data pipelines and processing workflows to improve performance, scalability, and overall efficiency</li><li>Implement data quality checks and validation logic to ensure data accuracy, consistency, and completeness</li><li>Create and maintain documentation including data mappings, data definitions, architectural diagrams, and data flow diagrams</li><li>Develop proof-of-concepts to evaluate and validate new technologies, tools, or data processes</li><li>Deploy, manage, and support code across non-production and production environments</li><li>Investigate, troubleshoot, and resolve data-related issues, including identifying root causes and implementing fixes</li><li>Identify performance bottlenecks and recommend optimization strategies, including database tuning and query performance improvements</li></ul>

<p>Qualifications</p><ul><li>Bachelor’s degree in Computer Science, Data Science, Software Engineering, Information Systems, or a related quantitative discipline</li><li>4+ years of experience in data-focused roles such as Data Engineer, ETL Engineer, Data Architect, or similar</li><li>Active Databricks Data Engineer or Analyst certification</li></ul><p>Technical Skills & Experience</p><ul><li>4+ years of hands-on experience developing in Python</li><li>3+ years of experience working with Databricks, including production implementations involving data structures, data storage, change data capture, pipeline optimization, and best practices</li><li>3+ years of experience with Kimball dimensional modeling, including star schemas, fact tables, Type 1 and Type 2 dimensions, aggregates, and a strong understanding of ELT/ETL methodologies</li><li>3+ years of experience writing complex SQL and PL/SQL</li><li>2+ years of experience using Airflow for workflow orchestration</li><li>3+ years of experience working with relational databases (Oracle or similar platforms)</li><li>2+ years of experience with NoSQL databases such as MongoDB, Cosmos DB, DocumentDB, or comparable technologies</li><li>2+ years of cloud platform experience (Azure or equivalent)</li><li>Experience implementing CI/CD practices using Git-based workflows and DevOps tools</li><li>Familiarity with modern data storage formats including Parquet, Arrow, and Avro</li></ul><p><br></p>

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