<p><strong>Data Pipeline Development &amp; Integration</strong></p><ul><li>Design, build, and maintain scalable ETL/ELT pipelines to extract, transform, and load data from multiple sources.</li><li>Develop automated data integration solutions supporting enterprise applications, analytics, and reporting.</li><li>Integrate structured and semi-structured data from APIs, relational databases, cloud platforms, and third-party systems.</li><li>Develop batch and real-time data processing solutions.</li><li>Troubleshoot pipeline failures, data inconsistencies, and performance bottlenecks.</li></ul><p><strong>Data Warehousing &amp; Architecture</strong></p><ul><li>Design and optimize enterprise data warehouses, data lakes, and lakehouse architectures.</li><li>Develop efficient data models, schemas, and transformations to support business intelligence and analytics.</li><li>Build and maintain cloud-based data solutions using AWS, Microsoft Azure, or Google Cloud.</li><li>Optimize SQL queries, database performance, and data processing workloads.</li><li>Implement data partitioning, indexing, and storage optimization strategies.</li></ul><p><strong>Data Quality &amp; Governance</strong></p><ul><li>Develop automated data validation, monitoring, and quality assurance processes.</li><li>Ensure data accuracy, consistency, reliability, and availability across enterprise systems.</li><li>Implement data governance standards, access controls, and security best practices.</li><li>Maintain documentation for data pipelines, architecture, and transformation logic.</li><li>Support compliance with organizational data privacy and security requirements.</li></ul><p><strong>Cloud Engineering &amp; Automation</strong></p><ul><li>Develop and maintain cloud-native data pipelines and processing workflows.</li><li>Utilize orchestration tools such as Apache Airflow, Azure Data Factory, or similar technologies.</li><li>Implement CI/CD practices for data engineering workflows.</li><li>Automate data processing, monitoring, and infrastructure deployment.</li><li>Collaborate with DevOps and infrastructure teams to improve scalability and reliability.</li></ul><p><strong>Analytics &amp; AI Support</strong></p><ul><li>Partner with business intelligence and analytics teams to deliver reliable datasets for reporting and dashboards.</li><li>Develop curated data models supporting Power BI, Tableau, and other visualization platforms.</li><li>Build data pipelines supporting machine learning, predictive analytics, and AI applications.</li><li>Collaborate with AI engineers and data scientists to prepare, transform, and deliver data for model development and production applications.</li><li>Identify opportunities to improve business processes through better data integration and automation.</li></ul><p><br></p><p><br></p>

<ul><li>Bachelor&#39;s degree in Computer Science, Information Technology, Data Engineering, or a related field, or equivalent practical experience.</li><li>3–5+ years of professional experience in data engineering, database development, or related roles.</li><li>Strong proficiency in SQL and Python.</li><li>Hands-on experience developing ETL/ELT pipelines and data integration solutions.</li><li>Experience working with relational databases such as SQL Server, PostgreSQL, Oracle, or MySQL.</li><li>Experience with cloud platforms such as AWS, Azure, or Google Cloud.</li><li>Knowledge of data warehousing concepts, dimensional modeling, and database optimization.</li><li>Experience with data orchestration and scheduling tools.</li><li>Familiarity with REST APIs, JSON, and other data integration methods.</li><li>Experience with Git, CI/CD, and software development best practices.</li><li>Strong analytical, troubleshooting, and communication skills.</li></ul><p><br></p>

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