Top Remote Data & Analytics Jobs

Leads actuarial financial data systems and marts, developing data solutions, extracts, reports, analyses, automations, validations, and executive reporting support. Manages data mart maintenance, audits, business requirements, technical specifications, user acceptance testing, and system implementations. Provides technical leadership, coordinates vendors and departments, trains junior staff, and advises project teams on data architecture, business rules, configuration, and financial data quality.

Supports information collection and organization for manuals, training materials, installation guides, proposals, and reports. Edits technical and customer-facing documentation, assists with financial and administrative tasks, and maintains systems, operations, and procedural documentation libraries. Collaborates remotely with project managers, requirements analysts, Scrum Masters, developers, testers, and government stakeholders in Agile ceremonies while complying with CUI and cybersecurity requirements.

Supports business intelligence reporting and data needs using Power BI, SQL Server, SSAS, DAX, T-SQL, ETL processes, and JD Edwards data. Prepares reports, dashboards, extracts, and analytics; maintains existing BI solutions; handles support tickets; troubleshoots routine data and ERP issues; validates and translates ERP data; and escalates complex architecture, integration, security, and performance issues.

Designs, develops, and maintains scalable Azure data pipelines and ETL/ELT solutions using Python, Scala, Spark, and Azure data services. Responsibilities include optimizing distributed processing, managing data quality and validation, monitoring and troubleshooting pipelines, supporting production deployments, and collaborating with architects, analysts, and cross-functional teams. The role also requires Hadoop experience, Control-M workflow orchestration, SQL performance tuning, and adherence to testing, version control, and CI/CD practices.

Manage Epic Cogito reporting projects for healthcare organizations by gathering requirements, designing and developing reports, performing testing and validation, and providing post-implementation support. Collaborate with internal and external stakeholders, solve complex problems, and manage multiple projects independently while delivering healthcare IT and analytics solutions.

The Director of Biostatistics leads statistical strategy and analysis for clinical trials in oncology, collaborating with clinical teams and regulatory bodies.

Build and maintain scalable data pipelines, ETL workflows, databases, and cloud-based data storage for digital marketing data. Ensure data quality, accuracy, and performance while preparing datasets for dashboards and reporting. Collaborate with analysts, CSMs, leadership, and cross-functional teams to address data needs, troubleshoot issues, participate in code reviews, and support scalable data management processes.

Supports the Product Innovation Team by modifying and optimizing SQL queries, visualizing data with BI tools, identifying insights, and analyzing enhancements. Participates in coding, testing, documentation, and discussions while providing customer service and managing multiple tasks. The internship requires at least 30 hours per week and emphasizes advanced Excel and visualization skills, plus familiarity with Python and SQL.

Build and maintain FinOps data pipelines, BigQuery and dbt models, cost attribution systems, forecasting and anomaly detection models, and cost-versus-revenue analytics. Identify and implement AWS and GCP savings opportunities, automate governance with Python, Terraform, and Lambda, and partner with Engineering, Finance, Product, and leadership on cloud costs, forecasting, reporting, and architecture decisions.

Designs, builds, and maintains scalable ETL and data processing pipelines supporting analytics, forecasting, risk, and customer insights. Leads complex SQL development, data modeling, governance, quality, lineage, security, and compliance. Partners with engineering, finance, sales, compliance, product, analysts, and data scientists to translate requirements into reliable workflows. Evaluates emerging technologies, leads proof-of-concepts, and develops automated solutions using Python, Spark, Databricks, cloud platforms, orchestration tools, and modern data warehouses.