Top Senior Data & Analytics Jobs

Own email marketing analytics across campaigns, audiences, segments, and lifecycle programs. Investigate engagement, fatigue, conversion, and testing results; build dashboards and reports; validate data accuracy; resolve tracking issues; and translate findings into recommendations. Present insights to clients, guide measurement strategies, establish reporting standards, and collaborate with email, technical, and client teams.

Build customer-facing data products for the single-family rental market. Responsibilities include architecting real estate data models, designing reliable data pipelines and workflows, shaping data platform architecture, establishing engineering standards, and developing real estate domain expertise. The role partners with data science and product teams and requires leadership in scalable data engineering.

Design, build, optimize, and maintain scalable batch and real-time data pipelines, data models, schemas, and storage systems. Ensure data quality, reliability, performance, and secure delivery across platforms. Collaborate with data scientists and analysts, troubleshoot data systems, evaluate emerging technologies, and mentor junior engineers. The role is onsite in a SCIF supporting STRATCOM and requires Top Secret/SCI clearance.

Designs and implements scalable data pipelines, cloud data platforms, storage solutions, and analytics infrastructure. The role focuses on Snowflake and AWS architecture, migrating legacy systems to cloud environments, developing Python and SQL data-processing logic, orchestrating workflows, and implementing Infrastructure-as-Code and CI/CD. The engineer also contributes to data governance, quality, observability, stakeholder communication, mentoring, and technical leadership.

Leads institutional research and data operations, analyzing university data, creating executive reports and visualizations, managing databases and archival information systems, and ensuring state and federal reporting compliance. Supervises staff, oversees department hiring and development, manages budgets, supports data-driven decision-making, documents reporting processes, and develops technology enhancements. The role requires advanced SQL and WebFOCUS querying, statistical analysis, data visualization, confidentiality, and collaboration with university stakeholders.

Conduct independent cost analysis and develop lifecycle cost estimates for Army acquisition programs. Forecast future system and program costs, create methodologies and models, advise on budgets and resource allocation, analyze Earned Value Management reports, and prepare executive briefings and milestone-review documentation. The role requires ACE-IT modeling, Army acquisition knowledge, strong communication, independent judgment, and an active Secret clearance in Huntsville, Alabama.

Build, deploy, and support scalable data pipelines and curated data products on Azure Databricks. Integrate enterprise data sources using batch and streaming patterns, transform data with SQL and Python/PySpark, and implement Delta Lake, dimensional modeling, governance, monitoring, testing, and CI/CD. Collaborate with technical and business stakeholders to deliver reliable, documented data products for analytics, reporting, and AI use cases while improving platform performance, security, quality, and cost efficiency.

Analyzes complex data to identify fraud trends and develops, tests, implements, and optimizes fraud rule strategies for new account originations. Evaluates rule performance, thresholds, segmentation, and treatment strategies; conducts champion/challenger testing; and delivers actionable recommendations. Collaborates with operations, technology, risk management, and compliance teams to improve fraud detection while balancing mitigation, customer experience, false positives, and operational efficiency.

Leads Flexential’s enterprise data strategy, architecture, governance, integration, analytics enablement, and information management functions. Oversees data platforms, warehouses, pipelines, APIs, data products, metadata, lineage, quality, security, and governance standards. Builds an enablement-focused operating model, partners with AI and business teams, manages vendors and budgets, and develops the Enterprise Data team. The role drives trusted, reusable data assets, self-service analytics, operational efficiency, and AI readiness while improving platform reliability, delivery discipline, and measurable business outcomes.

Partners with data product owners, technical teams, and business stakeholders to identify data and analytics needs, define requirements, create user stories and acceptance criteria, and support backlog prioritization. Manages analytics support requests, investigates recurring issues and root causes, maintains legacy-report inventories, and recommends modernization and data-quality improvements. Supports adoption through documentation, training, communications, and outcome measurement while helping transition users to governed data products and self-service technologies.