Top Senior Data & Analytics Jobs in New Orleans, LA

The Senior Analyst will support the personalization algorithm by conducting analyses, testing features, managing projects, and collaborating with teams to improve food recommendations for customers.

Own Silver and Gold medallion-layer modeling and semantic layer governance using dbt and SQL. Improve warehouse performance and cost, standardize BI tooling, collaborate with stakeholders to produce trusted metrics, troubleshoot data quality, and evolve analytics platform.

Supports strategic planning through business intelligence, data integration, data modeling, reporting, dashboards, forecasting, and analytics solutions. Acquires and validates healthcare claims, demographic, provider, regional, and service-line data; monitors data quality and reporting processes; troubleshoots issues; documents methodologies; and partners with BI developers and cross-functional teams to maintain scalable enterprise analytics capabilities.

Designs, develops, and optimizes the enterprise data warehouse and ETL processes. Performs data modeling, cleansing, SQL optimization, documentation, and provides technical guidance to support reporting and analytics.

Develop and support Informatica ETL solutions (70% development, 30% support). Build error-handling frameworks using schedulers (Autosys/Control-M/Tidal). Work with PowerCenter grid, IDQ, MDM, Informatica Cloud; perform performance tuning, Unix scripting, Teradata/SQL development, and data cleansing, standardization, and profiling.

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.