<p><strong>Robert Half is working with a client who is looking to hire a Data Engineer</strong> to support a growing enterprise data and analytics initiative. This individual will help build and modernize the data pipelines, integrations, and cloud-based data infrastructure used across the organization.</p><p>The ideal candidate has experience working with large datasets, modern cloud data platforms, and production-grade ETL/ELT pipelines. This role will work closely with Data Architects, Analytics Engineers, BI teams, and business stakeholders as the organization expands its enterprise data capabilities.</p><p>Responsibilities</p><ul><li>Design, build, and maintain scalable ETL/ELT data pipelines.</li><li>Integrate structured and unstructured data from multiple enterprise systems.</li><li>Develop and optimize data models used for analytics and reporting.</li><li>Build solutions within cloud data environments such as Azure, AWS, or GCP.</li><li>Monitor data pipelines for performance, reliability, and data quality.</li><li>Partner with analysts, architects, and application teams to understand data requirements.</li><li>Support the migration of legacy data workloads to modern cloud platforms.</li><li>Develop reusable frameworks and automation for data processing.</li></ul><p><br></p>

<p><br></p><p>Qualifications</p><ul><li>4+ years of experience in Data Engineering or a similar role.</li><li>Strong SQL and Python skills.</li><li>Experience with technologies such as Databricks, Snowflake, Azure Data Factory, AWS Glue, or similar tools.</li><li>Experience developing ETL/ELT pipelines.</li><li>Understanding of dimensional modeling and modern data architecture.</li><li>Experience working with APIs and enterprise application integrations.</li><li>Familiarity with Git, CI/CD, and DevOps practices.</li></ul><p>Experience supporting large-scale data modernization or cloud migration initiatives is highly preferred.</p>

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