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4 results for Data Processor Remote Position in Chattanooga, TN
- Charlotte, NC
- remote
- Permanent / Full Time
- 0 - 0 USD / Yearly
- <ul><li>Design, develop, and optimize data pipelines using Azure Data Services (Azure Data Factory, Azure Data Lake Storage, Azure Synapse).</li><li>Build and maintain scalable ETL/ELT workflows using Databricks (Spark, PySpark, Delta Lake).</li><li>Implement and manage data orchestration and dependency management using Dagster or similar tools.</li><li>Partner with analytics, data science, and product teams to ensure reliable, high-quality data availability.</li><li>Optimize data models and storage strategies for performance, scalability, and cost efficiency.</li><li>Ensure data quality, observability, and reliability through monitoring, logging, and automated validation.</li><li>Support CI/CD pipelines and infrastructure-as-code practices for data platforms.</li><li>Enforce data security, governance, and compliance best practices within Azure.</li></ul>
- 2026-04-22T00:00:00Z
- Grandville, MI
- remote
- Temporary to Hire
- 40 - 55 USD / Hourly
- We are looking for a skilled Data Engineer to join our team in Wyoming, Michigan. This Contract to permanent role offers an exciting opportunity to design, manage, and optimize data architecture and engineering solutions across a dynamic healthcare organization. The ideal candidate will play a key role in ensuring efficient data governance and infrastructure performance while collaborating with cross-functional teams.<br><br>Responsibilities:<br>• Develop and maintain robust data architectures and frameworks, including relational and graph databases, to meet business objectives.<br>• Create and manage data pipelines to extract, transform, and load data from various sources into data warehouses.<br>• Ensure data governance policies are implemented and monitored, including retention and backup protocols.<br>• Collaborate with teams across departments to translate business requirements into technical specifications.<br>• Monitor and optimize the performance of data assets, identifying opportunities for improvement.<br>• Design scalable and secure data solutions using cloud-based platforms like AWS and Microsoft Azure.<br>• Implement advanced tools and technologies, such as AI, to enhance data analytics and processing capabilities.<br>• Mentor and support team members by sharing technical expertise and providing guidance.<br>• Establish key performance indicators (KPIs) to measure database performance and drive continuous improvement.<br>• Stay up to date with emerging trends and advancements in data engineering and architecture.
- 2026-04-24T00:00:00Z
- Houston, TX
- remote
- Temporary / Contract
- 39 - 44 USD / Hourly
- <p>Position Overview</p><p>We are seeking a delivery‑focused Data Automation Engineer to design and implement innovative automation solutions across a Microsoft Azure‑based data analytics platform. This role partners closely with engineering teams and stakeholders to translate business requirements into scalable data engineering and AI‑enabled solutions.</p><p>The ideal candidate is hands‑on with Azure Data Factory, Synapse Pipelines, Apache Spark, Python, and SQL, and brings experience building reliable ETL pipelines across SQL and NoSQL environments. This role emphasizes performance optimization, automation, and proactive data quality within Agile DevOps delivery models.</p><p><br></p><p>Key Responsibilities</p><p>Data Engineering & Automation</p><ul><li>Develop high‑performance data pipelines using Azure Data Factory, Synapse Pipelines, Spark Notebooks, Python, and SQL.</li><li>Design ETL workflows supporting advanced analytics, reporting, and AI/ML use cases.</li><li>Implement data migration, integrity, quality, metadata, and security controls across pipelines.</li><li>Monitor, troubleshoot, and optimize pipelines for availability, scalability, and performance.</li></ul><p>Performance Testing & Optimization</p><ul><li>Execute ETL performance testing and validate load performance against benchmarks.</li><li>Analyze pipeline runtime, throughput, latency, and resource utilization.</li><li>Support tuning activities (e.g., query optimization, partitioning, indexing).</li><li>Validate data completeness and consistency after high‑volume processing.</li></ul><p>Platform Collaboration & DevOps Support</p><ul><li>Collaborate with DevOps and infrastructure teams to optimize compute, memory, and scaling.</li><li>Maintain versioning and configuration control across environments.</li><li>Support production, testing, development, and integration environments.</li><li>Actively participate in Agile delivery processes including Program Increment planning.</li></ul>
- 2026-04-20T00:00:00Z
- Philadelphia, PA
- remote
- Temporary / Contract
- 50 - 55 USD / Hourly
- <p><strong>Data Scientist (Big Data) III – Contractor</strong></p><p><strong>Employment Type:</strong> 27 Week Contract, Potential for Extension or Conversion</p><p><strong>Location: </strong>MUST CURRENTLY RESIDE in Philadelphia Region</p><p><strong>Employment Type:</strong> Contract / Temporary</p><p><strong>Pay: </strong>Available on W2 </p><p><strong>Position Overview</strong></p><p>The Senior Data Scientist (Big Data) will support large‑scale data science initiatives by designing, developing, and deploying advanced analytical and machine learning solutions. This role collaborates closely with data engineers, analysts, software developers, and business stakeholders to deliver scalable, production‑ready data products that drive data‑informed decision making.</p><p>The successful candidate will apply statistical modeling, machine learning, and big data technologies to solve complex business problems, while also providing technical guidance and mentorship across project teams.</p><p><strong>Key Responsibilities</strong></p><ul><li>Lead complex, cross‑functional data science initiatives delivering solutions across multiple technologies and platforms.</li><li>Design, develop, and deploy data mining, statistical, machine learning, and graph‑based algorithms for large‑scale data sets.</li><li>Partner with data engineering teams to ensure proper implementation, performance, and operational use of analytical solutions.</li><li>Review and assess data science programs and models at an enterprise level to evaluate suitability, performance, and scalability.</li><li>Build and maintain scalable big‑data analytics solutions supporting accurate targeting, forecasting, and advanced insights.</li><li>Develop and support end‑to‑end machine learning pipelines, including data preparation, training, testing, validation, and deployment.</li><li>Establish performance metrics, monitoring, and evaluation procedures for models in production.</li><li>Translate complex analytical findings into clear, actionable insights for technical and non‑technical stakeholders.</li><li>Provide mentorship and technical guidance to junior team members.</li><li>Contribute to data strategy, methodology selection, and continuous improvement of analytics capabilities.</li><li>Support testing, validation, and user acceptance activities to ensure alignment with business requirements.</li><li>Perform additional related duties as needed to support analytics and data initiatives.</li></ul>
- 2026-04-20T00:00:00Z