Leads the technical direction of a data semantics team while designing and scaling semantic infrastructure across observability platforms. The role requires Staff-level architectural ownership, cross-team influence, hands-on distributed-systems experience, and mentorship.

Build scalable data pipelines, infrastructure, and quantitative models that support experimentation, forecasting, and business decision-making. The role requires 4+ years of production data engineering experience, strong Python and SQL skills, distributed computing expertise, and a quantitative degree.

Own financial data integration pipelines and scalable data models supporting accounting, billing, revenue, and financial reporting. The role requires 8+ years of data or software engineering experience, strong cloud warehouse and data infrastructure expertise, and the ability to lead cross-functional initiatives.

Senior Data Engineer responsible for designing and deploying scalable data infrastructure, orchestration models, and analytics tooling to enable data-driven decisions, ML products, and enterprise reporting at Vanta. Requires 4+ years data experience, software engineering mindset, modern data stack proficiency, and passion for secure, compliant data systems.

Senior Analytics Engineer responsible for designing complex data models, building scalable SQL pipelines, enabling AI tooling, and improving data infrastructure to support self-serve analytics, dashboards, and data science at Vanta. Requires 4+ years data experience, software engineering mindset, and expertise with modern analytics tools like dbt.

The Senior Engineer will build, deploy, and support scalable Workato-based integrations across GTM business systems, particularly Quote-to-Cash workflows. The role requires 5+ years of enterprise integration experience, strong API and scripting skills, and expertise in monitoring, security, and CI/CD practices.

Own Polymarket’s analytics modeling layer, transforming trading and application data into trusted datasets, standardized metrics, and self-serve reporting. The role requires 7+ years of experience, expert SQL, dbt or equivalent modeling experience, orchestration, cloud warehouse expertise, and strong dimensional-modeling skills.

Build and evolve large-scale data collection infrastructure and architectures supporting user behavior data, personalization, and recommendation systems. The role requires strong Java and SQL experience, JVM-based data processing expertise, and familiarity with cloud, Kubernetes, and modern engineering practices.

Build and scale distributed data ingestion, standardization, and big-data pipelines while improving platform reliability, security, and cost controls. The role requires 8+ years of data engineering experience, technical leadership, cloud deployment expertise, and strong customer-facing communication.

Leads data governance and security across the lakehouse, analytics stack, and internal data products, establishing classification, access, quality, and compliance controls. Requires 5+ years in data governance, data security, GRC, or privacy engineering and experience with modern data platforms and audits.

Build and operate the data platform and pipelines that support billing, financial reporting, product analytics, and operational decisions. The role requires strong Python, SQL, data modeling, cloud data platform, orchestration, and infrastructure-as-code experience.

Builds governed Silver and Gold data models, semantic assets, and reusable transformation patterns on Databricks for business domains such as finance, RevOps, marketing, and HR. Requires 5+ years in analytics or data engineering, strong SQL and dimensional modeling expertise, and effective stakeholder collaboration.

Build and scale data architecture, governance, and ETL pipelines across Snowflake, Databricks, and cloud platforms. The role requires 3+ years of data engineering experience, strong API and pipeline expertise, and the ability to collaborate across technical and business teams.

The Analytics Engineer will own OnePay’s analytical data foundation, building trusted dbt models, tests, documentation, dashboards, and semantic metrics on Databricks. The role requires at least three years of analytics engineering experience, expert SQL and dbt skills, strong data-quality practices, and hands-on use of AI coding tools.

Builds and deploys real-time clinical data integrations between EHR systems and a healthcare platform. The role requires 3+ years of production data pipeline experience, Python, cloud and relational database expertise, integration testing, and deployment support.

Build and evolve reliable analytics infrastructure, pipelines, schemas, and foundational datasets supporting quantitative research across strategies. The role requires strong Python and SQL skills, distributed data-platform experience, and ownership of observability, performance, and reproducibility.

Builds and maintains finance data pipelines, applications, dashboards, and AI-assisted tools on the Databricks platform. The role requires 7+ years of experience across finance systems, data engineering, analytics engineering, or finance and accounting, plus strong SQL and Python skills.

Leads architecture and delivery of complex finance data pipelines, AI use cases, and internal applications while partnering with Accounting, FP&A, and Finance leadership. Requires 12+ years of data engineering or finance systems experience, strong SQL/Python and Databricks expertise, and deep finance-domain knowledge.

Design and develop next-generation database query and storage systems, covering optimization, distributed execution, transactions, and physical data organization. The role requires 5+ years of related systems experience and values expertise in databases, distributed systems, or performance optimization.

Leads the design and operation of Databricks’ large-scale Data Intelligence Platform, including metrics stores, ETL frameworks, multi-cloud pipelines, governance, and infrastructure tooling. Requires extensive industry experience, distributed-systems expertise, and technical leadership across complex data infrastructure initiatives.

Build and operate Databricks’ company-wide Data Intelligence Platform, including metrics stores, ETL frameworks, orchestration, governance, and reliable multi-cloud data pipelines. The role requires 6+ years of industry experience and technical leadership on large-scale data infrastructure projects.

Leads the design, operation, and evolution of Databricks’ cross-company Data Intelligence Platform, including large-scale data systems, pipelines, governance, and infrastructure. Requires 10+ years of distributed-systems experience and substantial technical leadership on production data platforms.

Leads Mercury’s data engineering organization and long-term platform strategy, building reliable, governed infrastructure and reusable data products for analytics, AI, operational systems, and self-service. Requires 10+ years of relevant experience, including 5+ years leading data or engineering teams.

Own medium-range demand forecasts for Anthropic's expanding infrastructure fleet across accelerators, CPU, storage, network, and managed services. The role requires hands-on SQL/Python modeling, large-scale infrastructure planning experience, and partnership with sourcing, Finance, and efficiency teams.

Build and maintain trusted data models, pipelines, dashboards, and workflows across Product and GTM. The role requires 5+ years of analytics or data engineering experience, exceptional SQL, strong dbt and cloud warehouse expertise, and sound analytical judgment.

Builds and scales the analytical data foundation across business and product teams, owning dbt models, Snowflake, Python/Airflow pipelines, reconciliation, data quality, and semantic layers for AI tools. Requires 5+ years of analytics or data engineering experience with strong SQL, dbt, Python, and SaaS data expertise.

Leads architecture and delivery of large-scale advertising data systems, including off-platform integrations, cleanroom workflows, taxonomy automation, and measurement pipelines. The role requires 8+ years of backend or data engineering experience, strong Python, data-platform expertise, privacy knowledge, and hands-on AI-assisted development.

Leads the technical strategy, governance, and quality of Discord’s analytical data infrastructure, building trusted curated datasets and metric frameworks for internal and externally reported analytics. Requires 7+ years in data and software engineering, expert SQL, strong Python, and experience operating data systems at scale.

Builds reliable data models, pipelines, metrics, dashboards, and automation that support Sales and Customer Success. The role requires strong SQL and analytical modeling skills, experience with cloud warehouses and ELT/ETL workflows, Python proficiency, and cross-functional communication.

Owns the architecture and operation of a scalable data platform, designing Airflow pipelines, improving reliability and cost efficiency, and leading cross-team technical initiatives. Requires 7+ years of data engineering experience, production container infrastructure expertise, and strong architectural leadership.

Designs and operates scalable enterprise data pipelines, warehouses, and lakehouse infrastructure using Python, SQL, dbt, Airflow, and Snowflake. The role requires 8+ years of data engineering experience, production ownership, cloud expertise, and strong architectural and mentoring skills.

Leads architecture and delivery of Instacart’s open lakehouse foundation, governance controls, and multi-engine compute strategy. Requires 10+ years building production-scale data infrastructure or distributed systems, with expertise in lakehouse, streaming, and platform migrations.

Builds scalable data-processing, reconciliation, and regulatory-reporting solutions for Compliance, Finance, and Treasury workflows. The role requires at least five years of software development experience, strong Python and SQL skills, Snowflake expertise, and technical leadership capabilities.

Leads architecture and development of large-scale financial data management infrastructure, setting technical direction across major initiatives and mentoring engineers. Requires 12+ years of distributed-systems and architecture experience, deep big-data expertise, and broad technical leadership.

Build and operate highly available datastore infrastructure and platform tooling supporting Auth0’s large-scale services. The role requires 5–8 years of software development experience, infrastructure automation expertise, cloud experience, and familiarity with databases and reliability engineering.

Leads the architecture, modeling, pipelines, quality systems, and certification processes for a canonical compliance data platform. Requires 8+ years in analytics or data engineering, expert SQL and Python, modern warehouse expertise, and technical leadership under regulatory pressure.

Leads architecture and implementation for Cloudflare’s company-wide data infrastructure, including pipelines, data products, governance, and access services. Requires 8+ years building data infrastructure at scale, strong backend programming skills, and experience leading cross-functional technical initiatives.

Leads architecture and operations for Cribl’s data platform, including Snowflake, Prefect, dbt, AWS infrastructure, ingestion services, and AI-ready data workflows. The role requires deep Snowflake expertise, strong Python and SQL skills, infrastructure-as-code experience, and the ability to mentor engineers and set technical direction.

The Senior Data Engineer builds and operates large-scale data pipelines and foundational data products for healthcare claims, EHR, and reference datasets. The role requires advanced Python and SQL, Airflow, distributed processing, AWS, production troubleshooting, and strong data reliability practices.

Leads architecture and operation of a petabyte-scale data lake platform, including Iceberg metastore services, object storage abstractions, migrations, authorization, and compliance controls. Requires 10+ years of software engineering experience and a track record with large-scale distributed storage or data infrastructure.

Leads engineers building and operating large-scale data discovery, metadata, catalog, pipeline, and warehouse systems while improving data quality and governance. Requires 10+ years of data-systems experience, distributed-systems expertise, backend programming, strong SQL, and technical leadership.

Leads technical delivery for scalable data systems, pipelines, warehouses, and supporting applications while mentoring engineers and partnering cross-functionally. Requires extensive experience with distributed data frameworks, backend development, SQL, data quality, and technical leadership.

Leads a team delivering reliable, scalable data pipelines, warehouses, and supporting applications for critical product-risk use cases. The role requires 10+ years building and operating data systems, distributed data-processing expertise, backend programming, strong SQL, and technical leadership.

Build and own data pipelines, models, marts, and services supporting Product, Data Science, and go-to-market teams. The role requires 6+ years of software engineering experience, distributed data processing expertise, backend development skills, and strong SQL.

Build and own Teleport’s internal data platform, including pipelines, warehouse architecture, data models, and quality controls. The role partners with product, engineering, finance, and revenue teams and requires strong SQL, Python or Go, cloud warehouse, and data governance experience.

Builds and owns scalable data pipelines, models, and integrations supporting Lyft’s Safety and Customer Care platforms. The role requires 4+ years of data engineering experience, strong Spark, Python, and SQL skills, and familiarity with distributed data systems and AWS tooling.

Build scalable reporting, data processing, and metrics delivery systems for Instacart’s advertising platform. The role requires 5+ years of software engineering experience, distributed systems expertise, strong SQL, and experience with data technologies such as DBT and Airflow.

Builds and delivers human-data projects, evaluation strategies, and tooling that improve AI model training signals and quality. The role requires cross-functional engineering collaboration, dataset analysis, and experience with Python, SQL, annotation workflows, or machine-learning evaluation.

Builds secure, observable data models and ELT pipelines for cyber insurance and cybersecurity analytics, while enabling BI and AI-driven risk scoring. The role requires Snowflake, dbt, Python, LookML, secure data-handling practices, and relevant cybersecurity or cyber insurance experience.

Owns Silver- and Gold-layer data modeling, semantic-layer governance, warehouse performance, and BI enablement for trusted self-service analytics. The role requires 5–7+ years of analytics engineering experience, strong SQL and dbt expertise, cloud warehouse optimization, and cross-functional stakeholder partnership.