Top Data & Analytics Jobs

Build and maintain scalable BigQuery data solutions, including tables, views, stored procedures, and data models. Manage SQL deployment manifests and multi-environment rollouts through GitLab CI/CD. Improve data quality, governance, performance, security, and accessibility across large-scale datasets. Collaborate with architects, data scientists, engineers, and global stakeholders while contributing to AI-enabled initiatives, code reviews, technical leadership, and team mentoring.

Lead and grow a global data engineering team while establishing foundational data platforms and engineering standards. Design and oversee GCP-based pipelines, medallion data models, DataOps, monitoring, SLAs, CI/CD, governance, and data quality practices. Drive AI adoption across engineering workflows and build reliable, AI-ready data. Partner with business and technology stakeholders to prioritize roadmaps, deliver scalable solutions, and support data democratization.

Lead the architecture, development, and scaling of data pipelines and infrastructure for a customer-facing Data Lake platform. Build ETL and ingestion systems using GCP, Debezium, Pub/Sub, Dataflow, BigQuery, Python, Golang, and SQL. Establish engineering standards, deliver strategic projects, mentor engineers, influence cross-functional technical decisions, optimize data services, and shape the platform roadmap.

Designs, builds, operationalizes, and maintains scalable GCP data pipelines and warehouses. Responsibilities include ETL optimization, data modeling, governance, lineage, quality checks, monitoring, alerting, documentation, and troubleshooting. The role uses Python, SQL, BigQuery, dbt, Airflow, Dataflow, and related tools to integrate data from multiple sources and support analytics and reporting. It also requires collaboration with stakeholders, reusable software components, and ownership of production data pipelines.

Designs and leads scalable GCP data platforms, pipelines, models, and ETL workflows across ingestion through consumption. Owns BigQuery architecture, performance, cost optimization, data quality, governance, observability, testing, CI/CD, and monitoring. Establishes engineering standards, evaluates technologies, shapes the technical roadmap, and mentors engineers. Partners with technical and business leaders to solve complex data problems and translate ambiguous needs into reliable analytics solutions.

Lead product analytics for a B2B SaaS product: define metrics and measurement frameworks, analyze user behavior and product performance, build self-service dashboards, partner cross-functionally to link usage to business outcomes, and translate data into strategic recommendations for product roadmap and GTM decisions.

Lead and build a product analytics function: define KPI framework, instrumentation, and self-serve analytics using Pendo and BI tools. Partner cross-functionally to measure product performance, surface insights, influence roadmap and embed AI-powered analytics into product lifecycle.

Develop standardized reporting, dashboards, KPIs, and actionable business insights using data from Salesforce, billing, product usage, login, and marketing systems. Automate recurring reporting, improve data consistency, document reporting structures, and connect insights to commercial actions such as retention cases. Partner with finance, IT, FP&A, and go-to-market teams to gather requirements, test solutions, and deliver scalable reporting that improves customer health, adoption, retention, and business results.

Lead design and rollout of a fit-for-purpose data governance program: manage data lifecycle, implement governance frameworks and tools, drive data catalogs/lineage, upskill stewards, define KPIs, and partner cross-functionally to improve data quality, compliance, and usability.

Lead and grow a team of data engineers to design, build, and operate scalable ETL/ELT pipelines and medallion architectures on GCP. Drive DataOps, monitoring, data quality, IaC, and AI adoption while translating business goals into data solutions and ensuring production reliability and governance.