Top Data & Analytics Jobs

Build and maintain Databricks data pipelines, ETL/ELT processes, SQL transformations, and Power BI dashboards for HR and People Analytics. Ensure data quality, optimize models and reporting performance, troubleshoot issues, document solutions, and collaborate with HR stakeholders and technical teams to deliver scalable workforce analytics.

Collect, verify, and organize precinct-level election returns; summarize and visualize turnout and performance trends; produce reports for candidates and campaign teams; maintain data confidentiality. Training and support provided; volunteer role.

Manage end-to-end data operations, including collection, processing, delivery, pipeline optimization, and data quality monitoring. Collaborate with engineering, product, and operations teams to improve data workflows, identify inefficiencies, and implement scalable solutions. Analyze data to provide actionable insights for decision-making and AI model development while communicating technical issues to non-technical stakeholders.

Develop and maintain advanced visual analytics applications, large relational databases, and enterprise data systems. Responsibilities include creating analytics for structured and semi-structured data, designing database strategies and standards, integrating systems with data warehouses, and improving performance and functionality. The role requires Perl, Python, PL/SQL, PostgreSQL, and AWS experience, along with an active Top Secret/SCI-eligible clearance and potential CI polygraph eligibility.

Analyze financial and operational data, build reliable data pipelines and metrics, investigate incidents, perform root-cause analysis, and improve complex workflows. The role supports process automation, documentation, technical training, stakeholder communications, and deployment of automated solutions. It requires strong SQL skills, financial systems experience, operational problem-solving, and collaboration with technical and non-technical teams.

Designs, develops, and maintains scalable ETL pipelines, data lakes, warehouses, and integrated data solutions. The role includes requirements analysis, Agile collaboration, testing, debugging, documentation, cloud data engineering, and optimization of reliable and performant systems. It requires strong Python, SQL, database, distributed processing, data engineering, software development, and cloud platform skills, along with effective communication and problem-solving abilities.

Develop and support Qlik solutions across the full application lifecycle, including requirements analysis, data integration, scripting, modeling, transformation, testing, deployment, troubleshooting, and production support. The role emphasizes Qlik Cloud modernization, automation, cloud connectivity, enterprise data sources, and scalable technical solutions. It also requires collaboration with stakeholders and technology teams, documentation, standards development, continuous improvement, and identifying opportunities to apply AI and automation.

Processes and validates financial, payroll, ledger, time-tracking, expense, project, and operational data. Converts information into accurate workbooks, templates, reports, and organized deliverables while maintaining employee, project, and expense records. Researches relevant company and industry information, organizes audit documentation, supports interview qualification summaries, and manages multiple data requests and deadlines in a remote environment.

Leads supply chain analytics, reporting, automation, and Power BI solutions while managing product readiness portfolios for launches and product changes. Coordinates cross-functional deliverables, governance forums, SKU readiness, risk escalation, documentation, and milestone tracking across commercialization projects. Translates business needs into scalable analytics and digital solutions, communicates insights, and drives stakeholder adoption and operational improvements.

Manage enterprise data-use requests and privacy reviews while supporting data governance, security, access management, and regulatory compliance. Analyze data using BigQuery, Alteryx, R, Python, SQL, PostgreSQL, and MongoDB. Collaborate with legal, business, security, risk, and technology stakeholders to implement privacy safeguards, support GDPR and CCPA audits, improve governance processes, and ensure responsible data use across Ford.