Top Data & Analytics Jobs in Memphis, TN

Leads and develops the Data Engineering team while remaining hands-on with scalable pipelines, ETL/ELT processes, data warehouses, integrations, and infrastructure. Establishes architecture, reliability, quality, and performance standards; guides technical strategy; improves automation and monitoring; and partners with Finance and business stakeholders to translate data needs into practical solutions.

Lead enterprise Master Data Management strategy, architecture, governance, data quality, and integration initiatives across customer, product, supplier, employee, and financial domains. Design data models, hierarchies, matching and survivorship rules, integration patterns, and implementation roadmaps. Advise clients on Oracle and Salesforce ecosystems, lead workshops and executive presentations, guide solution delivery, mentor consultants, and contribute to proposals and statements of work.

Designs, develops, and maintains Databricks-based ETL pipelines, data lake architectures, datasets, and data warehouses supporting reporting, analytics, and AI/ML workloads. Troubleshoots and optimizes Databricks and SSIS processes, maintains SSRS reports, implements data quality controls, migrates legacy systems, and collaborates with business and technical teams. The role also promotes AI-assisted development practices and documents technical procedures.

Build and operate core data infrastructure for edge and hybrid environments, including ingestion, OT/IoT integrations, real-time streaming, data contracts, schemas, validation, lineage, observability, telemetry, and scalable query access. The role requires production ownership, reliability practices, customer integration, and collaboration across engineering and customer-facing teams. Candidates should have 6+ years of experience with production data, streaming, or integration systems and proficiency in Python and/or Go.

Designs, analyzes, documents, integrates, and migrates complex environmental datasets for AirHub business lines. Responsibilities include analyzing legacy databases, creating logical and physical data models, documenting mappings and business rules, developing migration specifications and API integrations, supporting data governance and testing, and producing technical documentation. The role also requires close collaboration with business stakeholders in an Agile delivery environment.

Analyze large, multi-source datasets to identify trends, risks, opportunities, and performance drivers. Build Power BI dashboards, reports, KPI scorecards, and analytics-ready datasets using SQL. Partner with business leaders and stakeholders to clarify questions, evaluate initiatives, maintain data quality, and develop actionable recommendations. Present insights through clear visualizations and data storytelling, while managing multiple analytics assignments and contributing to team best practices.

Designs enterprise-scale federated data architectures integrating Palantir Foundry and Databricks. Establishes data-sharing, governance, lineage, metadata, and ownership standards across cloud platforms. Leads legacy ETL modernization, builds scalable PySpark and Spark SQL pipelines, architects secure connectivity, and enables AI, machine learning, real-time analytics, and self-service data products. Serves as the technical authority, leads architecture reviews, and manages stakeholder relationships.

The Senior Data Analyst gathers business and data requirements, assesses data quality and sources, maintains data dictionaries and lineage, defines KPIs, validates reports, and delivers actionable insights. The role supports data governance, PII protection, integrations, data transformation, platform performance, business continuity, and process improvement. It collaborates with stakeholders and data teams, mentors colleagues, resolves complex issues, and contributes to enterprise data strategy and technology decisions.

Lead financial data engineering initiatives involving commissions, incentive programs, and backend financial systems. Build scalable, accurate, and reliable data pipelines, platform tooling, partner integrations, analytics infrastructure, and data science infrastructure. Shape technical strategy and roadmaps, collaborate with Finance, Product, Data Science, and Engineering, mentor engineers, contribute code, lead incident response, and establish engineering standards.

Supports the Transformation Office through enterprise KPI reporting, performance analysis, executive dashboards, governance materials, and strategic insights. The role identifies risks and opportunities, validates initiative updates, tracks decisions and action items, and prepares executive, board, and investor-ready reporting. It partners with Finance and senior leaders to connect transformation progress with business outcomes and uses Power BI to develop dashboards.