Top Senior Data & Analytics Jobs in New Orleans, LA

Leads Navitus’s centralized analytics team, delivering client performance analysis, financial modeling, underwriting support, pricing analysis, competitive intelligence, dashboards, and strategic recommendations. Partners with Sales, Finance, Clinical, Network Strategy, Account Management, and technical teams to support client growth, retention, RFPs, renewals, and market-facing engagements. Establishes data quality and governance standards, improves analytical processes, and mentors team members.

Build and maintain scalable batch and incremental data pipelines using Python, SQL, and Snowflake. Develop data warehouse models, transformations, automation, quality checks, lineage, alerting, and performance optimizations. Collaborate with analysts, data scientists, and application teams to deliver trusted datasets, while documenting pipelines, schemas, and data contracts.

Manage and modernize MySQL database environments supporting large-scale, multi-tenant applications. Monitor database health, performance, capacity, and availability; optimize SQL and troubleshoot production incidents. Support MongoDB operations, database scalability, monitoring through Datadog and Grafana, root-cause analysis, secure database practices, and safe database changes. Collaborate with application, platform, and engineering teams while using Jira and GitHub throughout the delivery lifecycle.

Build and maintain scalable batch and incremental data pipelines using Python, SQL, and Snowflake. Develop warehouse models, transformations, automation, data quality checks, lineage, alerting, and performance optimizations. Collaborate with analysts, data scientists, and application teams to deliver trusted datasets, while documenting pipelines, schemas, and data contracts.

Leads the design, delivery, and optimization of data architecture, pipelines, semantic layers, data quality frameworks, and Tableau BI platforms. Partners with stakeholders to manage requirements, project plans, sprint execution, monitoring, governance, and release delivery. Guides data engineers, manages team members, and supports AI-enabled analytics capabilities. Requires strong SQL, Spark, PySpark, SSIS, cloud data platform, CI/CD, Tableau infrastructure, and data engineering expertise.

Designs and maintains a scalable data platform supporting analytics, machine learning, and AI workloads. Builds tooling for reliable data pipelines, semantic layers, data agents, LLM applications, and evaluation systems. Ensures data quality, availability, observability, and reliability while establishing modeling, testing, and platform best practices. Collaborates with Data Science and Product Engineering, leads solutions from design through implementation, and contributes individually in a fast-paced startup environment.

Leads advanced analytics across the organization, owning MAU forecasting and growth models, experimentation standards, and causal inference methods. Establishes analytical best practices, reviews high-stakes analyses, partners with data and product teams, and scales recurring work through AI tooling. Mentors data professionals and translates complex statistical findings into actionable leadership recommendations.

Designs and optimizes enterprise data warehouse solutions, SQL queries, ETL workflows, and Tableau dashboards. Responsibilities include data ingestion, performance tuning, data quality validation, BI governance, documentation, and reporting automation using SQL, Python, and Tableau. The role collaborates with business partners to translate data needs into actionable insights and supports mission-critical analytics applications in a fully remote environment.

Own the technical design and operation of Palmetto’s governed data platform. Build trusted data products, semantic models, ingestion and transformation pipelines, secure access interfaces, and agent-ready data services. Establish governance, masking, authorization, observability, CI/CD, and audit readiness. Partner with finance, operations, product, and engineering teams while mentoring engineers and setting cross-team technical direction.

Leads and grows the data engineering team while owning enterprise data architecture, ingestion, modeling, semantic layers, governance, secure APIs, and reliable platform outcomes. Partners with finance, operations, sales, marketing, and product to deliver governed, traceable data for products and AI agents. Sets the roadmap, manages vendors and costs, reviews architecture, contributes code, and delivers cross-functional data platform projects.

Build executive-facing dashboards, scalable data models, semantic layers, and reporting datasets using dbt, Looker, and SQL. Analyze large datasets, identify trends and anomalies, manage the Looker analytics platform, resolve data quality issues, and deliver analytics initiatives across business domains. Partner with product, engineering, finance, and operations stakeholders to define metrics and reporting solutions. Mentor junior analytics engineers and improve analytics standards and documentation.

Lead Client Legal Services analytics strategy and team development. Own Power BI reporting products, Microsoft Fabric data solutions, governance, predictive modeling, responsible AI adoption, ROI measurement, and executive insights. Partner cross-functionally to improve legal operations, litigation outcomes, staffing, capacity, cost management, quality, and workflow optimization while building scalable analytics capabilities and institutional knowledge.

The Senior Data Analyst partners with business teams to define performance metrics, build and maintain self-service Hex dashboards, conduct exploratory analyses, and deliver actionable recommendations. The role coordinates with Engineering, Product, and Data teams to ensure reliable reporting data and contributes to dbt models. It also requires stakeholder communication, strategic insight generation, and translating technical findings for nontechnical audiences.