Top Consulting Data & Analytics Jobs in San Francisco, CA

The role involves leading Quote-to-Revenue processes, mentoring junior team members, and ensuring quality deliverables in finance systems and billing operations.

Develop and implement advanced algorithms, apply statistical techniques, collaborate with clients, assess technologies, and mentor team members.

Lead analytics implementations using Google Analytics and Tag Manager for clients, providing mentorship and managing projects with a focus on enhancing clients' digital strategies.

Design, build, and operate large-scale Hadoop-based data pipelines and streaming systems. Implement ETL/ELT with Spark, Hive, and Sqoop; optimize jobs for performance; manage storage layouts (HDFS, Hive, HBase, Parquet/ORC/Delta/Iceberg/Hudi); enforce data governance, monitoring, and orchestration (Airflow/Oozie); collaborate with analysts and data scientists; lead architecture reviews and mentor junior engineers.

Coordinate and drive data implementation projects by liaising with clients, vendors, and internal teams; maintain project documentation and trackers (Excel, Smartsheet); provide status updates, schedule calls, log issues, and ensure milestones are met while managing multiple priorities in a collaborative office environment.

Support projects by reviewing engineering documents, validating utility asset data, performing GIS functions (creating/updating maps and records), conducting QC, and producing reports and project tracking for client deliverables.

Support data-driven projects in pharmaceuticals, leading project teams, and providing insights through data analysis and collaboration with stakeholders.

Drive demand forecasting and business planning for VR headsets and wearables. Build and maintain sell-in/sell-through forecasts, analyze sales performance, identify risks and opportunities, develop forecasting models from large datasets, support production and launch decisions, present insights to leadership, and create reports and dashboards while partnering with cross-functional teams.

Design, build, and maintain data pipelines, ETL processes, and data warehousing solutions using Python and GCP/BigQuery. Ensure data quality, optimize storage and processing, support new data products, and mentor junior engineers while collaborating with the CTO and team.

Lead end-to-end EHS data programs: define scope, manage budgets and agile delivery, design data architectures, ensure data governance and compliance, build dashboards/automations (Tableau/Power BI), and mentor teams to deliver actionable environmental insights at scale.