Top Senior Data & Analytics Jobs

Design, build, and optimize scalable AWS and Snowflake data pipelines, databases, data models, and cloud-based solutions. Implement ETL/ELT workflows, data quality and monitoring frameworks, CI/CD pipelines, automated recovery, documentation, and performance improvements. Collaborate with stakeholders and cross-functional teams in an Agile environment while conducting advanced analysis using Python and SQL.

Develops market intelligence and analytical solutions using data mining, modeling, forecasting, scenario planning, and visualization. Partners with marketing, sales, supply chain, strategy, finance, and commercial stakeholders to manage data logistics, build data tools, validate outputs, identify market opportunities, and communicate actionable recommendations. Manages multiple projects, presents insights to executive audiences, and supports strategic decision-making.

Owns TrendAI’s AI-generated answer visibility measurement program, including baselines, prompt methodology, recurring reporting, citation and competitive analysis, and entity representation. Translates findings into actionable content, PR, social, and messaging recommendations, partners with cross-functional teams to implement them, and evaluates outcomes. Requires enterprise B2B technology experience, AI visibility expertise, marketing analytics, knowledge-graph familiarity, technical fluency, and people-leadership readiness.

Designs and maintains BI solutions, writes optimized SQL and stored procedures, and builds AI-assisted reports and dashboards using Power BI, Tableau, and Excel. Translates business questions into actionable insights for Sales and cross-functional teams, develops data models, supports reporting migrations, and ensures data quality, governance, documentation, and consistency across platforms.

Build and maintain scalable data platforms and systems that transform raw market data into validated analytical datasets, including bars, residuals, curves, volatility surfaces, and greeks. Collaborate with trading, research, and external vendor teams to understand datasets and workflows, implement calculations, document technical solutions, and ensure reliable delivery through strong testing and validation practices.

Conduct market and competitive intelligence across Autodesk’s industries, analyzing AI developments, competitors, startups, funding, products, partnerships, research, and regulations. Partner with research teams to define markets, size opportunities, map competitors, test assumptions, and synthesize qualitative and quantitative findings. Lead projects, manage contributors and timelines, produce executive-ready briefs and presentations, and improve intelligence systems and processes using AI and automation with appropriate human validation.

Leads the team responsible for the performance, availability, integrity, security, recovery, and scalability of Microsoft and Oracle databases. Establishes database strategies, optimization, patching, compliance, capacity planning, and disaster recovery processes. Oversees database design, data warehouse structures, licensing, upgrades, vendor relationships, and technical projects. Partners with infrastructure and operations teams, mentors junior DBAs, manages third-party resources, and supports mission-critical enterprise applications.

Leads end-to-end ETL processes, develops Power BI dashboards, and uses SQL and BigQuery to deliver business insights. Partners with stakeholders and executives to support strategic decision-making, communicates complex findings clearly, and mentors analysts on data analysis, ETL, and dashboard development best practices.

Owns portfolio-level project performance analytics, KPI development, dashboards, reporting systems, and data governance for a Power EPC organization. Develops executive reports, audits project data quality, leads performance reviews and process improvement initiatives, and supports automation, AI, and digital transformation efforts. Partners cross-functionally with engineering, supply chain, construction, project controls, and leadership to improve project delivery performance and decision-making.

Own and evolve the end-to-end product analytics platform, including instrumentation, event collection, ingestion, raw data storage, data pipelines, analytical models, metrics, dashboards, quality monitoring, observability, lineage, and governance. Partner with software engineers to ensure analytics data is accurate, scalable, traceable, and reliable for business and product decision-making.