Top Hybrid Data & Analytics Jobs

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.

Supports the Branch Operations Performance and Analytics team by researching data assets, documenting sources, lineage, retention, transformation logic, and KPIs. Processes and analyzes data, investigates accuracy issues, supports audits and access controls, monitors stakeholder requests, and contributes to data roadmap planning. Collaborates with data stewards, analysts, program managers, and business stakeholders while developing technical, analytical, and problem-solving skills.

Owns web and conversion analytics across the eCommerce journey. Analyzes customer behavior, funnels, campaigns, merchandising, retention, and commercial performance; builds dashboards and measurement plans; supports experimentation; validates tracking and data quality; develops forecasts and business cases; and presents actionable insights to senior leaders. Partners with cross-functional teams and mentors analysts while establishing analytics standards and best practices.

Designs, builds, and supports scalable data pipelines, integrations, transformations, and services for Mayo Clinic’s biomedical research platform. Works with genomic, omics, clinical, laboratory, imaging, and multimodal datasets; harmonizes data, maintains metadata and provenance, validates quality, and enables governed access. Partners with investigators, bioinformaticians, scientists, and analytics teams to support research, machine learning, and precision medicine applications using Google Cloud and modern data engineering tools.

Sources, prepares, validates, and analyzes data to produce business intelligence reports, analytical datasets, automated processes, and insights. Collaborates with business and technology partners to define needs, improve reporting workflows, and communicate findings. Uses queries, data visualization, automation, and predictive analysis techniques while mentoring junior staff and supporting data governance and compliance.

Design, deploy, and maintain global data platform infrastructure with emphasis on multi-region Databricks orchestration. Lead system architecture, optimize Databricks (Delta, Spark, Unity Catalog), implement IaC with Terraform, build CI/CD pipelines, troubleshoot platform issues, and collaborate with cross-functional teams to meet technical, governance, and performance requirements.

The Senior Data Analyst translates commercial business needs into technical data specifications, writes complex SQL queries, extracts and validates large datasets, and automates workflows with Python. The role delivers accurate analytics and reporting, communicates findings to technical and non-technical stakeholders, supports pre-sales and RFP activities, manages competing requests, and collaborates with Operations, Strategy, and Data Engineering teams.

The Data Analyst will analyze player behavior, web and game usage data, and business processes to generate actionable insights. Responsibilities include data exploration and validation, metric development, visualization, statistical analysis, experimentation, stakeholder collaboration, and presenting recommendations that improve user experience and business growth. The role also involves translating data needs into specifications and developing skills in data cloud technologies, data science, storytelling, and AI.

Build and maintain data products, dbt models, ELT pipelines, data warehouses, Looker explores, and visualizations. Drive analytics strategy, self-service BI, data governance, security, observability, lineage, and stewardship. Mentor engineers, apply software engineering practices, solve complex business problems, and collaborate cross-functionally. Lead AI-powered analytics improvements, including intelligent monitoring, automated data quality checks, responsible AI governance, and AI-assisted development.

Leads the Journey Intelligence Team’s analytical strategy, manages analysts, develops customer measurement frameworks and segmentation, conducts exploratory and experimental analysis, and translates customer behavior insights into strategic initiatives that improve engagement and the end-to-end customer experience.