Top Senior Data & Analytics Jobs in New Orleans, LA

Lead consumer insights projects from brief development through research design, quantitative and qualitative analysis, storytelling, reporting, and client presentation. Manage client relationships, develop actionable recommendations, create surveys, oversee project plans, and coach junior team members. Serve as a strategic advisor by translating consumer and market data into business decisions.

Build trusted GTM business intelligence by defining commercial metrics, analyzing performance across Sales, Marketing, Customer Success, Product, and Finance, diagnosing root causes, and delivering executive recommendations. Partner with data engineering and operations teams to integrate Salesforce, product, support, marketing, billing, and financial data. Evaluate AI-powered analytics capabilities and improve self-service decision-making.

Design, build, optimize, and operate enterprise cloud data platforms and Databricks ETL/ELT pipelines. Develop batch and streaming pipelines, data models, infrastructure-as-code solutions, BI dashboards, monitoring, and scalable ML models. Ensure platform reliability, governance, security, and compliance while collaborating with software, systems, product, and business teams.

Own end-to-end production data platforms, writing Python and SQL, designing AWS pipelines, modeling analytics data, and implementing quality and reconciliation controls. Make architecture decisions independently, ensure correctness and auditability, and use AI coding tools effectively. The role also supports applied AI initiatives including entity resolution, LLM-assisted analytics, embeddings, and anomaly scoring.

Staff Data Analyst leading complex, cross-functional analytics initiatives and executive-level decision support. Responsibilities include defining metrics, building scalable data models and infrastructure with dbt, ensuring data quality and governance, developing analytical roadmaps, mentoring analysts, improving data literacy, and advising Sales, Marketing, Finance, and Operations stakeholders.

Owns the end-to-end data platform, including Snowflake infrastructure, ingestion pipelines, Airflow orchestration, dbt transformations, governed gold-layer models, and metric definitions. Ensures reliability, performance, testing, documentation, governance, and CI/CD standards. Builds data systems from scratch, partners with analytics stakeholders, and uses AI-assisted development tools to accelerate engineering work. Requires strong SQL, platform ownership, software engineering practices, and experience with Snowflake, Airflow, and dbt.

Build network capacity and demand forecasts across 50 states, support clinician recruitment and retention analytics, measure clinical and scheduling outcomes, and design experiments with Product and Engineering. Develop governed data models, KPI definitions, and AI-powered analytics infrastructure. Serve as the primary analytics partner for Network leadership by translating complex, multi-source data into actionable recommendations and presenting insights to technical and executive audiences.

Build and maintain branch network performance reporting, dashboards, semantic models, and analytical datasets using SQL and Alteryx. Translate banker, branch, market, and enterprise data into actionable insights for senior leaders. Lead analytical projects, manage timelines, communicate executive-ready findings, improve reporting processes, and mentor junior analysts. Partner with Distribution and Consumer Bank leadership in a hybrid, primarily onsite environment.

Data Engineer II will modernize BlueLabs’ data platform by leading Kimball dimensional modeling and legacy warehouse migrations, building reliable production data pipelines, and enforcing data quality standards. The role requires advanced SQL, Python, and dbt expertise, hands-on Snowflake and Redshift experience, and ownership of testing, documentation, observability, and scalable architecture. The engineer will collaborate cross-functionally, guide Data Engineer I team members, contribute to architectural decisions, and translate business logic into maintainable, cloud-agnostic data layers.

Own analytics and reporting solutions for acquisitions, product launches, and other complex business events. Translate business changes into data models, system updates, processes, and reporting definitions. Coordinate Data Engineering, Analytics, Data Science, and Data Governance teams; lead cross-functional execution and establish a Business Intelligence Council. Partner across GTM, Finance, Product, IT, and other functions to reconcile metrics, clarify ownership, and maintain business visibility.