Top Senior Data & Analytics Jobs

Owns end-to-end warehouse transformations, curated analytical models, data governance, documentation, lineage, and data quality troubleshooting. Partners with business stakeholders to translate ambiguous questions into reliable models supporting product usage, customer adoption, account health, and go-to-market reporting. The role also improves data access, metric definitions, and self-service capabilities while using SQL, cloud warehouses, transformation frameworks, scripting, and BI tools.

Leads commercial analytics and self-service business intelligence using Power BI, Excel, SQL, CRM, ERP, and governed enterprise data. Develops dashboards, KPIs, forecasting analyses, profitability insights, and performance reporting while translating complex data into executive recommendations. Partners with Sales, Finance, Commercial Operations, IT, and Enterprise Data teams to improve data quality, reporting automation, decision-making, and analytics adoption.

Designs and executes large-scale data migrations and conversions into Fiserv products. Builds custom database solutions and reusable ETL tooling, ensures data integrity, supports integrations, and leads go-live troubleshooting and incident response. Collaborates with clients and product teams on requirements and technical designs, evaluates database technology components, and may assist with hiring and staffing allocation management.

Supports a Department of Defense project assessing service members’ fitness for duty and eligibility for disability separation or retirement. Analyzes systems and business data, identifies data frameworks, supervises personnel, and integrates system-level data requirements and architectures into enterprise architectures compliant with DoD regulations.

Build and maintain Tableau dashboards, certified semantic models, dimensional data models, and Snowflake data warehouses integrated with Aurora. Apply Python, SQL, version control, and CI/CD to analytics assets while ensuring data quality, governance, lineage, observability, performance, and scalability. Partner with stakeholders to translate reporting needs into trusted, self-service business intelligence.

Leads Northwest Bank’s enterprise data governance program, including data policies, quality rules, lifecycle management, metadata, master data, stewardship, governance tooling, and remediation. Facilitates Data Working Groups, investigates root causes, manages governance metrics and reporting, demonstrates tools, documents processes, and supports training. Partners across a matrixed organization to ensure data assets meet standards, controls, regulatory requirements, and business needs.

Lead data engineering initiatives for pharmaceutical and biotech clients by building cloud-based data pipelines, warehouses, processing systems, analytics, and visualization tools. Responsibilities include analyzing business requirements, transforming big data, identifying insights, advising on standards and best practices, estimating engineering efforts, collaborating with stakeholders and leadership, and supporting growth of the data science business.

Designs and leads scalable data architecture, pipelines, models, and governed Lakehouse datasets using Databricks, Spark, SQL, and Python. Owns ingestion through serving, data quality, monitoring, reliability, migrations, and production operations. Establishes reusable engineering standards, supports analytics and AI/ML use cases, makes architecture tradeoffs, and mentors engineers. Partners with product analytics stakeholders to translate business requirements into trusted datasets and influences technical direction across teams.

Lead and mentor an analytics engineering and data modeling team. Own the strategy, architecture, optimization, and governance of enterprise semantic layers and warehouse presentation models. Establish dimensional modeling, dbt pipelines, orchestration workflows, automated data quality testing, version control, and CI/CD practices. Partner with architecture, engineering, and business leaders to create scalable self-service data assets supporting BI, natural-language querying, anomaly detection, and AI-driven insights.

Design and maintain enterprise data architectures, databases, data models, warehouses, and integrations supporting Naval Shipyard maintenance operations. Ensure data quality, integrity, security, and recoverability across multiple Navy IT systems. Develop analytics, dashboards, visualizations, prediction tools, queries, and decision-support products for NAVSEA leadership. Collaborate with business analysts and software engineers, support lifecycle planning and portfolio architecture requirements, and participate in technical and metrics-focused user groups.