Top Data & Analytics Jobs

Leads advanced analytics for wireless offer performance and investment efficiency. Analyzes diverse data sources, evaluates profitability, customer quality, spend, growth, and forecast accuracy, and applies statistical, predictive, trend, and scenario modeling. Develops test-and-learn frameworks, dashboards, scorecards, and executive insights. Partners with Offer Strategy, Finance, Marketing, and leadership to guide offer design, targeting, pricing, budget allocation, forecasting, OEM negotiations, and investment decisions.

Manage cost-share and farm viability data in CRM and project management systems, maintain data protocols, develop collection tools, analyze program results, and prepare reports and maps for funders and partners. The role requires careful administrative coordination, compliance review, communication with farmers, and independent work planning. It is full-time with hybrid flexibility, a monthly Ames office requirement, and seasonal travel throughout Iowa and nearby states.

Sets technical direction and architectural coherence across Netflix’s Ads Data Engineering organization. The role guides cross-domain data system decisions, partners with engineering and business leaders, mentors data engineers, shapes platform-wide initiatives, and advances AI-native data engineering. Responsibilities span modern data foundations, ad-tech data flows, privacy and governance, platform migrations, scalable data products, and collaboration with Ads Platform Engineering, Data Science, and Product teams.

Designs, builds, and maintains scalable Databricks and PySpark data pipelines; develops Python and SQL transformations; identifies insights from ambiguous datasets; and ensures data quality, governance, documentation, and reliable delivery. Collaborates with stakeholders and cross-functional teams to integrate data into applications and dashboards, troubleshoot pipeline issues, and support a Department of Defense Navy client.

Owns production data systems end to end, including data models, ETL and API integrations, applications, platform maintenance, data quality, governance, and technical debt. Supports OPSDB and exploration operations, improves reliability and alerting, documents systems, collaborates with cross-functional and nontechnical stakeholders, and mentors junior analysts. The role also supports procurement and inventory initiatives, works with geologists, and requires occasional international travel to exploration sites.

Build and automate data tools, analytics libraries, dashboards, reports, and workflows for a systematic trading firm’s COO team. Integrate PostgreSQL, REST APIs, and Kafka data sources; develop AI-assisted natural-language data tools; automate recurring operational processes; perform ad-hoc analyses; and collaborate with technology, risk, operations, and execution teams to validate data quality and improve platform efficiency.

Develops and maintains automated data and analytical products for a government customer. Combines diverse intelligence and publicly available data sources, performs statistical analysis, creates production-quality software, manages version-controlled repositories, defines system requirements, tracks milestones, and validates system performance. Communicates technical findings and data products to technical and non-technical stakeholders, supporting time-sensitive operational decisions.

Own Marketing’s reporting and analytics layer by building executive dashboards, defining KPIs, modeling data across GTM systems, and establishing governance and trusted sources of truth. Partner cross-functionally to measure funnel performance, attribution, campaigns, pipeline, and ROI. Help evaluate and develop AI-powered analytics, conversational reporting, automated insights, and intelligent visualization while translating complex data into actionable recommendations for leadership.

Develop and operate scalable data pipelines, AI and data solutions, and interactive dashboards for federal financial management modernization programs. Collaborate with clients on data architecture and reporting needs, using Databricks or Palantir, Python, Spark, SQL, Qlik, Microsoft Power Platform, and Tableau. Apply AI and machine learning to automate metadata extraction, clustering, and dashboard scripting while delivering measurable client outcomes.

Designs and maintains scalable enterprise data architectures and ETL/ELT pipelines on Microsoft Fabric and Azure. Responsibilities include developing Python-based data solutions, optimizing Fabric warehouses and lakehouses, implementing governance, security, lineage, monitoring, and CI/CD, and integrating diverse data sources. The role partners with data science, machine learning, business intelligence, engineering, and business teams to support analytics and model training while improving platform reliability, scalability, and cost efficiency.