Top Data & Analytics Jobs

Designs and develops complex cloud-native data solutions, scalable batch and real-time pipelines, APIs, data models, and enterprise data platforms. Implements data governance, quality, lineage, security, observability, CI/CD, automated testing, and operational reporting capabilities. Collaborates with architects, product owners, analysts, governance, security, and platform teams on technology strategy and cloud modernization. Mentors engineers, leads technical design discussions, presents recommendations, and supports AI-ready data products and emerging development tools.

Design, build, and manage scalable batch and real-time data pipelines, databases, and processing systems. Develop and administer Databricks and Snowflake environments, optimize data architecture and distributed processing, manage PostgreSQL and MySQL databases, and implement governance, monitoring, alerting, and troubleshooting practices. Collaborate with analytics, engineering, and product teams to deliver reliable data solutions, document workflows, and promote modern data engineering practices.

Own GTM performance analytics, KPI and target setting, reporting, forecasting, compensation planning, and performance reviews across Sales and Post-Sales. Identify anomalies and optimization opportunities involving conversion, churn, productivity, pricing, packaging, segmentation, channel economics, and customer quality. Partner with Finance and GTM leaders to develop recommendations, lead strategic initiatives, and ensure data integrity while translating analysis into actionable business decisions.

Build and operate production-grade ELT pipelines from Benchling, Salesforce, and third-party systems into Snowflake using dbt. Own ingestion, transformation, warehouse, BI, governance, monitoring, testing, access controls, privacy, cost, and performance. Partner with AI engineering to provide trusted data for internal AI applications and agentic workflows, contribute to warehouse and metrics-layer architecture, and translate cross-functional stakeholder needs into scalable data solutions.

The Analytics Manager investigates business questions, delivers actionable insights, maintains data models and Looker dashboards, and communicates findings through presentations and visualizations. The role develops testing frameworks, subscription unit-economic models, marketing attribution, retention and cohort forecasts, and customer segmentation. It also partners with Product and Engineering to improve application tracking and customer behavior visibility.

As the first in-house Data Engineer, you will own the data infrastructure, build and maintain data pipelines, and collaborate with teams to ensure quality data access and insights.

Analyze transaction enrichment product performance, data quality, accuracy, match rates, and other metrics. Investigate anomalies in large datasets, build dashboards and automated alerts, improve QA processes and workflows, and develop documentation and monitoring standards. Partner with Product, Engineering, and AI/ML Data Science teams to translate insights into product improvements and automate recurring analytical work.

Maintains Baan databases, master files, label databases, prices, costs, part numbers, bills of materials, routings, and related manufacturing data. Audits database accuracy, documents changes, supports engineering changes and label updates, assists with quality procedures, and trains functional teams on Baan and associated databases. The role requires strong attention to detail, independent prioritization, database knowledge, and familiarity with manufacturing processes and ISO/IATF systems.

Lead a GTM Analytics team supporting Marketing, Sales, RevOps, and Customer Operations. Manage embedded analysts, establish trusted reporting and QA processes, review SQL and dashboards, guide funnel, campaign, sales, support, forecasting, segmentation, attribution, and experimentation analysis, and deliver executive recommendations. Partner with GTM leaders and data engineers, coach analysts, and develop self-service analytics, automation, governed dashboards, metric documentation, and AI-assisted workflows.

Owns RTB House’s performance media measurement strategy across products. Responsibilities include defining measurement taxonomies, evaluating attribution, incrementality, MMM, and MTA methodologies, managing third-party measurement partners, developing testing playbooks, piloting identity and measurement approaches, translating insights into market-facing messaging, and training commercial teams. The role requires hands-on performance media buying or oversight experience and strong ability to communicate measurement concepts, limitations, and results to technical, executive, and commercial audiences.