Top Remote Analysis Reporting Jobs in Memphis, TN

Leads the design, development, optimization, and migration of modern data platforms in Snowflake. Builds pipelines with dbt, Python, and cloud services; gathers client requirements; creates solution designs and project plans; advises on Snowflake performance, cost, security, and workload management; integrates BI, governance, and AI/ML tools; contributes to accelerators and mentors junior engineers. The role is remote, client-facing, consultative, and focused primarily on technical delivery rather than sales.

Build and operate batch and streaming data pipelines, ETL/ELT workflows, data warehouses, dimensional models, and reusable data services. Improve reliability, performance, quality, and cost efficiency through monitoring, testing, automation, and incident response. Partner with analytics, data science, product, business, platform, and infrastructure teams to deliver production data solutions and roadmap initiatives. Apply AI-assisted tools responsibly to development, testing, documentation, and troubleshooting.

Analyze telematics, IoT, sensor, and firmware data to evaluate hardware performance, reliability, and field issues. Build dashboards and reports, identify trends and anomalies, apply statistical and machine learning techniques, validate firmware improvements, and provide actionable insights to engineering, product, data science, and customer support teams. Help develop scalable data pipelines and promote data-driven hardware and software development.

Manages Finance analytics engineering and automation, building governed Snowflake and SQL data products, consumption layers, reconciliations, controls, workflows, and integrations. Partners with FP&A, Data Engineering, and business teams to translate Finance requirements into reliable technical solutions. Leads lineage analysis, testing, monitoring, documentation, AI-assisted workflows, production support, and team development while maintaining clear ownership between Finance and enterprise data teams.

The Associate Director will lead AHP’s analytics and data products domain, building curated datasets, transformation pipelines, semantic models, dashboards, and automated reporting. Responsibilities include delivering client and enterprise data products, establishing reporting standards, managing production refreshes and documentation, coordinating data engineering resources, and supporting AI initiatives. The role is hands-on, client-facing, and requires technical leadership across distributed project teams.

Leads Lexia’s business analytics and data strategy function, managing analysts and overseeing data engineering alignment. Owns BI strategy, Tableau governance, data governance, self-service dashboards, AI-enabled analytics, metric definitions, and data quality. Partners with Sales, Marketing, Customer Success, executives, and analytics engineering to translate business needs into insights, KPIs, models, and actionable recommendations. Manages analytics tools and vendors while ensuring responsible, secure, and effective use of enterprise data.

Designs and optimizes scalable data platforms, architectures, and production pipelines supporting AI and machine learning. Responsibilities include Databricks Lakehouse development, batch and real-time processing, data governance, security, monitoring, performance tuning, infrastructure planning, and collaboration with DevOps, MLOps, and cross-functional teams. The role serves as the AI team’s data engineering subject matter expert and ensures reliable, secure, cost-effective data solutions.

Lead the architecture and hands-on development of an AI-enabled data migration platform for legal software. Own extraction, transformation, orchestration, data quality, observability, and scalable go-live workflows. Partner with product management to define roadmap priorities, lead a focused engineering team, make architectural decisions, contribute code, and apply AI to migration assessment, mapping, validation, and automation.

Build and maintain dbt and semantic data models in Snowflake, develop ingestion and transformation pipelines, define trusted product metrics, and improve data collection. Partner with Product and Engineering to support experimentation and feature analysis. Establish data quality testing, documentation, HIPAA-aware access controls, and compliance practices. Use and validate AI-generated code and Snowflake Cortex outputs while raising technical standards across the team.

Build customer health scores, churn and expansion analytics, retention dashboards, automated alerts, and executive reports. Maintain integrations among databases, CRM, and BI tools while improving data quality and standardizing reporting. Lead AI adoption for analytics, validate generated insights, and enable customer-facing teams to make informed retention and expansion decisions. Requires strong BI, logistics or supply chain analytics, dashboarding, data integration, communication, and customer-focused skills.