<p><strong>Data Pipeline Development</strong></p><ul><li>Design, build, and optimize scalable ETL/ELT pipelines to support analytics and operational workflows.</li><li>Ingest structured, semi-structured, and unstructured data from multiple internal and external sources.</li><li>Automate and orchestrate data workflows using tools like Airflow, Azure Data Factory, AWS Glue, or similar.</li></ul><p><strong>Data Architecture & Modeling</strong></p><ul><li>Develop and maintain data models, data marts, and data warehouses (relational, dimensional, and/or cloud-native).</li><li>Implement best practices for data partitioning, performance optimization, and storage management.</li><li>Work with BI developers, data scientists, and analysts to ensure datasets are structured to meet business needs.</li></ul><p><strong>Cloud Engineering & Storage</strong></p><ul><li>Build and maintain cloud data environments (Azure, AWS, GCP), including storage, compute, and security components.</li><li>Deploy and manage scalable data systems such as Snowflake, Databricks, BigQuery, Redshift, or Synapse.</li><li>Optimize cloud data cost, performance, and governance.</li></ul><p><strong>Data Quality & Reliability</strong></p><ul><li>Implement data validation, error handling, and monitoring to ensure accuracy, completeness, and reliability.</li><li>Troubleshoot pipeline failures, performance issues, and data discrepancies.</li><li>Maintain documentation and data lineage for transparency and auditability.</li></ul><p><strong>Collaboration & Cross‑Functional Support</strong></p><ul><li>Partner with product, engineering, and analytics teams to translate business requirements into technical solutions.</li><li>Support self-service analytics initiatives by preparing high-quality datasets and data products.</li><li>Provide technical guidance on data best practices and engineering standards.</li></ul><p><br></p><p><br></p>
