Top Data & Analytics Jobs

Two-year early talent program developing data engineering professionals. Responsibilities include building and maintaining scalable data pipelines, integrating and transforming data, developing data models, implementing quality checks, and supporting data governance. The role uses SQL, Python, cloud platforms, and modern data engineering tools while collaborating with engineers, analysts, and business partners on production data solutions.

Leads the Analytics Systems Team of 6–10 engineers, overseeing team development, engineering quality, project delivery, product direction, roadmap prioritization, and strategic analytics infrastructure. The role guides development of data pipelines, analytics tooling, feature stores, and foundation-model integrations supporting clinical trials, diagnostics, biomarker discovery, and regulated Life Sciences workflows.

Own marketing analytics, reporting, dashboards, metric definitions, and customer attributes. Connect Google Analytics, HubSpot, and Salesforce data; support segmentation, campaign measurement, funnel reporting, and data-quality improvements. Partner with Marketing, Data, Revenue Technology, Product, and Engineering to translate business needs into reliable reporting and actionable insights.

Collects, cleans, integrates, and analyzes business data; develops Power BI dashboards, reports, models, pipelines, and data quality controls. Translates business needs into analytical solutions, identifies trends and recommendations, validates results, supports migrations and modernization, and explores AI and machine learning use cases. Partners with technical and nontechnical stakeholders while documenting data lineage, assumptions, governance, privacy, and responsible AI practices.

Optimize onsite search, navigation, taxonomy, and digital merchandising to improve product discovery and conversion. Analyze large datasets and KPIs, build dashboards, run A/B tests, and implement search relevance changes (boosts, synonyms, redirects) in partnership with merchandising, product, UX, IT, and vendor partners to increase ecommerce revenue and engagement.

The Data Engineer Intern will onboard and model datasets on cloud data platforms, build reliable ETL/ELT pipelines, and deliver high-quality data layers for analytics, reporting, and AI/ML workloads. Responsibilities include working with Databricks or Spark, cloud platforms, relational and NoSQL databases, data quality frameworks, version-controlled data models, Git, CI/CD, and modern development workflows. The intern will collaborate with AI, data, and finance professionals in a team environment.

Leads and builds Instructure’s decision science function, including hiring, team development, roadmap ownership, experimentation, causal and predictive modeling, executive insights, and data literacy. Partners with product, engineering, marketing, finance, and executives to guide product, pricing, retention, go-to-market, and operational decisions. Establishes analytical standards, supports data infrastructure, and ensures ethical, privacy-conscious use of student data.

Analyzes complex data to identify trends, challenges, and opportunities supporting tactical and strategic business decisions. Develops data collection systems, performs statistical analysis, creates reports and dashboards, and delivers end-to-end analytic solutions. Collaborates with business and technical teams to understand objectives, improve data quality, and provide actionable insights using business intelligence tools, databases, reporting packages, and data modeling techniques.

The Relationship Manager serves UHNW clients, enhancing client satisfaction, managing operations, and implementing advanced planning techniques. They aim to drive retention and growth in the Wealth Management Team by fostering client relationships and optimizing services.

Leads teams delivering IT solutions and manages architecture, systems analysis, development, integration, deployment, maintenance, budgets, vendors, and technical support. Assesses business and client requirements, develops technology plans, ensures architectural compliance, resolves technical issues, coordinates software and hardware implementations, monitors performance, and manages training. Supervises staff, oversees hiring and performance management, negotiates contracts, and partners with business units on technology strategy and investments.