Top Data & Analytics Jobs

Leads enterprise data visualization strategy across Finance, Operations, and IT. Manages visualization specialists, establishes dashboard governance, and delivers scalable dashboards and reporting solutions. Partners with executives and technical teams to define KPIs, optimize data models, ensure data integrity, and enable self-service analytics. Supports budgeting, forecasting, and performance management while driving automation, advanced analytics, and adoption of visualization best practices.

Build and operate production-grade AML data products, ETL pipelines, data models, integrations, and ML-ready datasets. Ensure data quality, lineage, security, governance, observability, reliability, and regulatory compliance. Support transaction monitoring, customer segmentation, risk rating, sanctions screening, and financial crime prevention initiatives. Lead architecture decisions, production support, incident response, CI/CD improvements, automated testing, code reviews, mentoring, and engineering standards.

Collects, organizes, cleans, and analyzes business data; reviews data accuracy and completeness; prepares reports, dashboards, and summaries; identifies trends supporting business decisions; and maintains spreadsheets and databases. The role is fully remote, includes paid training, and requires strong communication, organization, attention to detail, and independent work capability.

Leads integration of healthcare payer feeds and internal enterprise data into WellBe’s data platforms. Responsibilities include data mapping, transformation, validation, normalization, quality monitoring, governance, metadata and lineage management, requirements gathering, and supporting ingestion pipeline delivery. The role partners with engineering and analytics teams, serves as a subject matter expert, and ensures reliable data for value-based care, reporting, and operational use cases.

Leads data engineering strategy and mentors an analytics engineering team. Designs scalable ELT pipelines, warehouse integrations, data models, API ingestion workflows, and data quality frameworks using cloud and database technologies. Conducts exploratory analysis, supports dashboards and analytical solutions, monitors warehouse performance and costs, and ensures data governance, security, and compliance. Collaborates with data scientists, analysts, engineers, and business stakeholders to deliver healthcare analytics solutions.

Designs and maintains ELT pipelines, warehouse integrations, data models, and data quality processes. Collaborates with data scientists, analysts, engineers, and stakeholders to deliver scalable analytical solutions. Responsibilities include data integration, governance, security, performance optimization, exploratory analysis, visualization, and cloud-based API ingestion. Requires strong SQL, DBT, Snowflake, Azure Data Factory, cloud, and scripting experience, plus leadership and communication skills.

Manages data, databases, reports, SharePoint content, agreements, invoices, and technology-transfer records for a biomedical research organization. Supports CRADA funds and payments, invention disclosures, licensing, intellectual property evaluation, collaborator negotiations, outreach, training, and portfolio tracking. Serves as a liaison with researchers, leadership, information management, finance, and overseas laboratories. Requires biomedical research-environment experience, database and Microsoft Office proficiency, and eligibility for a Top Secret clearance.

Design, build, and maintain scalable cloud data lake infrastructure supporting analytics, reporting, and AI/ML. Develop batch and real-time ETL/ELT pipelines, data quality frameworks, governance policies, metadata and lineage systems, security controls, monitoring, disaster recovery, and performance optimization. Collaborate with IT, analytics, operations, and AI teams to ensure data integrity, compliance, accessibility, and effective use of enterprise datasets.

Performs business analysis and quality assurance for Murex data management initiatives in investment banking. Responsibilities include clarifying requirements and field definitions, validating data integrity and sources, running SQL analyses, documenting process flows and specifications, supporting testing and UAT, and assisting with data migration to Snowflake. The role collaborates with business and technology stakeholders to define controls, remediate issues, and support system implementation.

Build and support a Databricks-based cloud data platform for cashflow aggregation at a global bank. Responsibilities include collecting real-time and batch data, cleaning and enriching datasets, storing aggregated results in Delta Lake, supporting migration and integration, managing costs and use-case prioritization, and collaborating with data providers and consumers. The role also requires financial-services domain knowledge, communication, and leadership during the bank’s transition to Databricks.

Designs and optimizes batch and streaming data pipelines, cloud data warehouses, dimensional data models, and ETL/ELT processes at terabyte scale. Troubleshoots pipeline issues, improves infrastructure reliability and performance, implements data quality and governance practices, and supports privacy compliance. Collaborates with analysts, data scientists, and stakeholders to translate business needs into technical solutions. Leads and mentors data engineers, documents systems, and evaluates emerging technologies.

Owns and enhances a SQL Server-based data warehouse, ETL, and reporting platform supporting screening operations, billing, compliance, and customer reports. Designs SSIS packages and SSRS reports, develops optimized T-SQL, models relational schemas, resolves production issues, tunes performance, manages environment changes, and maintains auditability. Partners with product, QA, and business teams, reviews code in Azure DevOps, mentors junior engineers, and uses AI-assisted development tools.

Supports data management, integration, quality improvement, analytics, reporting, dashboard development, and automation initiatives. Responsibilities include consolidating and validating data, writing SQL queries, conducting exploratory analysis with Python or R, developing Power BI or Tableau dashboards, streamlining data pipelines, automating recurring tasks, and documenting processes.