Top Senior Data & Analytics Jobs

The Senior Data Analyst transforms complex mortgage, financial, and operational data into actionable insights for the Mortgage Partnership Finance program. Responsibilities include portfolio and risk analysis, forecasting, dashboard and scorecard development, automated reporting, data validation, governance, and executive presentations. The role collaborates with Risk, Finance, Business Intelligence, Data Management, Member Services, and Mortgage Operations teams while mentoring junior analysts and interns.

Leads the Bank’s mortgage analytics and insights organization, overseeing managers and analysts who evaluate MPF and residential mortgage portfolios. Provides strategic analysis of portfolio performance, credit and market risks, mortgage trends, and regulatory developments. Advises senior leaders, regulators, rating agencies, and the Board; oversees reporting, regulatory submissions, advanced analytics, AI, automation, and process improvements. Responsible for organizational design, talent development, performance management, succession planning, and executive communication.

Creates and maintains complex database reports, data extracts, and Power BI dashboards for court staff and programs. Documents reporting requirements, analyzes business data needs, performs functional testing and validation, troubleshoots SQL and database issues, improves stored procedures, and supports report deployment. Collaborates with stakeholders and database administrators to develop reporting solutions and provides dashboard guidance to judicial staff.

Lead enterprise Procure-to-Pay data initiatives, governance, and quality across Global Supply Management. Manage Data Analysts, analyze source systems (ERP, planning, WMS, shop floor), drive root-cause analysis, data migrations, validations, and process improvements to ensure accurate master and transactional data supporting planning, logistics, manufacturing, and digital transformation.

Drive mobile app growth through ad-hoc SQL analysis, dashboards, and BI tools; partner with CEO/CFO to provide insights, streamline ETL/ELT pipelines, and optimize user acquisition, retention, and monetization.

Leads the Data Engineering and Analytics team, setting strategy, managing intake and prioritization, mentoring staff, and ensuring reliable governed data products. Oversees Python, SQL, dbt, Airflow, and BigQuery pipelines; improves reporting, data quality, and operational processes; and guides predictive analytics and machine-learning initiatives. Partners with executives, product, operations, clients, and vendors while supporting monthly reporting, invoices, scorecards, and responsible handling of healthcare data and PHI.

Leads the Data Engineering and Analytics team, setting strategy, managing staff, prioritizing requests, and ensuring reliable governed data products. Oversees Python, SQL, dbt, Airflow, and BigQuery pipelines; improves reporting, invoicing, data quality, and operational processes. Guides predictive and prescriptive analytics initiatives, including forecasting, recommendation engines, and segmentation models, with responsible healthcare data governance. Partners with executives, product, operations, clients, and vendors while mentoring team members and driving AI-assisted development.

Lead and grow a Data Engineering & Analytics team to deliver governed, reliable data products. Own data pipelines, dbt models, BigQuery, Airflow, and Python-based tooling; manage intake/prioritization (Jira); advance analytics from reporting to predictive/prescriptive models; ensure PHI-safe practices, stakeholder alignment, and on-time delivery of reports, invoices, and analytics.

Own the end-to-end analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business problems and metrics, build reports, analyze data, design experiments, surface insights, and drive recommendations through execution. Partner with product, growth, finance, and operations leaders to influence decisions and improve key business outcomes.

Embed with a core business area to define problems, build reports and experiments, analyze data, surface insights, and drive high-impact recommendations end-to-end across growth, product, AI, or partnerships.

Partner with cross-functional teams to drive data-driven growth: design and analyze A/B tests, leverage machine learning for insights, define acquisition and partnership levers, and automate processes to improve operational efficiency.

Designs, implements, modernizes, and operates enterprise-scale economic data systems across ingestion, transformation, storage, quality validation, metadata, semantic modeling, visualization, dissemination, monitoring, and governance. Builds secure, scalable data products using modern cloud, lakehouse, warehouse, and distributed-processing technologies. Establishes DataOps, CI/CD, observability, lineage, and compliance controls; supports AI, machine learning, forecasting, and semantic search use cases; manages platform availability, infrastructure, roadmap, incidents, and stakeholder coordination.

Leads the strategy, architecture, and execution of an enterprise data platform supporting analytics, machine learning, operational systems, and AI applications. Manages and mentors data platform engineers while remaining hands-on with architecture, reliability, technical direction, and troubleshooting. Oversees pipelines, orchestration, governance, security, observability, data contracts, migrations, and platform operations. Partners cross-functionally to translate business needs into scalable technical solutions and communicates decisions to technical and non-technical stakeholders.

The Data Audit Manager evaluates data management, governance, processing, reporting, analytics, controls, access management, and data lineage within complex environments. The role reviews Python and SQL logic, database systems, Alteryx workflows, and reporting processes; supports regulatory remediation and issue validation; tests control effectiveness; and documents findings and recommendations for technical and non-technical stakeholders.

Evaluate data management, reporting, and analytics controls for a large financial services client. Review data transformations, Python code, SQL queries, DBMS and Alteryx workflows, assess data lineage and access controls, validate remediation activities, test control effectiveness, and document findings and recommendations.

Develop and maintain Tableau and other BI dashboards, reporting applications, data models, and ad hoc reports. Translate business requirements into technical specifications, perform ETL and SQL-based data analysis, optimize BI environments, and support the full reporting application lifecycle. Collaborate with architects, business teams, and developers to improve data-driven processes, resolve reporting issues, implement standards, and provide training and technical support.

Develops business intelligence and analytics solutions, including reports, dashboards, data marts, metadata layers, and decision-support applications. Analyzes data needs, designs dimensional and relational models, evaluates BI technologies, creates architecture documentation, and supports production troubleshooting. Partners with business and IT teams, manages small to midsize project scopes, establishes development standards, and mentors BI and analytics staff on tools, design practices, and data modeling.