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2 results for It Business Intelligence Analyst in Memphis, TN
- Memphis, TN
- onsite
- Permanent / Full Time
- 100000 - 120000 USD / Yearly
- <p><strong>Data Pipeline Development & 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 & 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 & 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 & 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 & 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>
- 2026-11-03T00:00:00Z
- Memphis, TN
- onsite
- Temporary / Contract
- 70 - 85 USD / Hourly
- We are seeking a highly skilled Big Data Engineer to design, build, and optimize scalable data platforms that support enterprise analytics, reporting, machine learning, and business intelligence initiatives. The ideal candidate will have experience developing large-scale data pipelines, managing cloud-based data ecosystems, and implementing high-performance data solutions that enable data-driven decision-making across the organization. Key Responsibilities Design, develop, and maintain large-scale data processing systems and data pipelines. Build and optimize ETL/ELT workflows for structured, semi-structured, and unstructured data sources. Develop scalable solutions using distributed computing frameworks such as Apache Spark, Hadoop, and Kafka. Collaborate with Data Scientists, Analysts, Architects, and business stakeholders to support analytical and operational requirements. Integrate data from multiple internal and external systems while ensuring data quality and integrity. Design and implement cloud-native data solutions within AWS, Azure, or Google Cloud environments. Monitor, troubleshoot, and improve the performance, reliability, and scalability of data platforms. Implement data governance, security, compliance, and access control standards. Support real-time and batch data processing requirements. Document architectures, workflows, and technical specifications to ensure operational excellence.
- 2026-11-09T00:00:00Z