Top Remote Analysis Reporting Jobs in New Orleans, LA

Build and maintain large-scale data processing pipelines using Apache Spark (PySpark/Scala) and Python. Design ETL workflows, implement distributed data processing, use version control (Git), and work with cloud platforms (GCP/AWS/Azure).

Lead Workday reporting strategy for higher education: design Advanced, Matrix, Composite, and Dashboard reports; implement row-level security and role-based access; partner with HR/Finance/Payroll/Institutional Research; support regulatory and executive reporting; manage testing, validation, and user training while ensuring governance and data standards.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Analyze complex content, datasets, research questions, and logical problems; verify claims through online research; summarize information; evaluate and correct AI-generated responses; and create annotations and scenarios to improve large language model performance. The role is fully remote, full-time for 16 weeks, requires U.S. English fluency, independent work, strong analytical and research skills, and an existing Gemini account with relevant conversation history.

Build and operate data-intensive web products and APIs, extend high-throughput ETL pipelines and scrapers, ensure reliability/observability, design self-scaling services, participate in code review, and collaborate across product, data, and infrastructure teams to meet production SLAs.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

Build and maintain ETL/ELT pipelines, ingest and transform structured and unstructured data, integrate APIs and external sources, improve data quality and monitoring, support dashboards and ML pipelines, optimize warehouse and cloud performance, and contribute to data governance and documentation.

Leads complex private banking data management and analytics initiatives, defining data strategies, quality standards, product attributes, and integrated client views. Partners with business, engineering, analytics, AI, and Wealth teams to translate needs into dashboards, KPIs, predictive models, personalized insights, and intelligent decision-making capabilities. Serves as a subject matter expert on private banking products while mentoring junior team members and enabling platform readiness.

Supports DHA MEPRS cost-accounting activities through recurring data processing, validation, reconciliation, analysis, reporting, and customer support. Extracts and analyzes personnel, workload, financial, and other datasets using SAS, Excel, and reporting repositories. Investigates data-quality issues, troubleshoots root causes, documents findings, develops recurring and ad hoc analytical products, communicates results, and improves or automates processes.

Support design, development, and maintenance of data pipelines and infrastructure. Assist with ETL/ELT workflows, data ingestion, cleaning, validation, modeling, and warehousing. Document processes and collaborate with data teams to support analytics use cases.

Performs advanced product and business analytics for a consumer mobile app, including experimentation, statistical analysis, metric development, dashboards, and leadership-ready insights. Partners with Product, Engineering, Finance, Data Science, and Analytics teams to guide strategy and feature iteration. Works independently with large datasets, communicates tradeoffs clearly, and uses AI-assisted tools to improve analytical efficiency.