Build and own trusted marketing analytics data models and pipelines supporting attribution, paid marketing, SEO, and retailer marketing. The role requires 3+ years of analytics or data engineering experience, strong SQL and dimensional modeling skills, and hands-on experience with dbt, Snowflake, and Airflow.

Build and scale secure, cloud-native data pipelines and orchestration systems for healthcare imaging, biomarkers, analytics, and AI. The role requires Python, SQL, Airflow or similar orchestration, cloud platforms, Databricks, and distributed processing experience.

Build and operate large-scale revenue data pipelines powering billing and cost attribution, while improving reliability, latency, and correctness. The role requires strong Spark and Airflow experience, cross-functional problem-solving, and operational ownership of mission-critical production systems.

Leads the design and development of scalable analytic data infrastructure, including the foundation for Celonis’s Digital Twin. Requires 10+ years of analytics or data engineering experience, enterprise Databricks expertise, and strong stakeholder communication.

Staff Data Engineer leading data platform initiatives across batch, streaming, real-time pipelines, data lake infrastructure, governance, and privacy. Requires 5+ years of data engineering experience, strong Spark and distributed processing expertise, and the ability to lead complex production systems.

Build and operate Jump’s Snowflake and dbt data platform, including ELT pipelines, governance, testing, monitoring, and analytics models. The role requires 6+ years of data engineering experience, production-grade SQL and Snowflake expertise, deep dbt knowledge, and strong Python and software engineering practices.

Build and operate trusted, scalable data-platform capabilities spanning warehousing, orchestration, governance, BI, and developer tooling. The role requires senior software engineering experience, strong Python skills, modern data-platform expertise, and Terraform proficiency.

Own the performance, availability, backup and recovery, upgrades, and observability of high-throughput PostgreSQL environments across on-premises infrastructure and Amazon RDS. The senior role requires production Patroni failover experience, deep PostgreSQL expertise, Linux fundamentals, software development proficiency, and strong documentation skills.

Build and operate reliable, production-grade data pipelines, warehouse infrastructure, and trusted datasets supporting company-wide analytics and AI initiatives. The role requires 3+ years of production data engineering experience, strong SQL and Python skills, and experience with Snowflake, dbt, cloud infrastructure, and orchestration.

Leads large-scale advertising data ingestion, measurement, and agentic workflow systems, combining deep ad-tech expertise with production LLM experience. Requires 10+ years of engineering experience and technical and people leadership in complex enterprise environments.

Build and own the data platform powering regulatory reporting for a federally regulated prediction-markets business. The role combines dbt and SQL engineering, automated validation, root-cause investigations, audit support, and direct collaboration with regulators and compliance.

Build and operate the data platform supporting automated regulatory reporting for a prediction markets business. The role combines SQL and dbt development, end-to-end data investigation, automated validation, and cross-functional ownership under strict deadlines.

Staff Data Platform Engineer leading the architecture and development of financial data infrastructure for revenue reporting, billing, forecasting, and compliance. Requires 8+ years of data engineering or architecture experience, strong streaming and warehouse expertise, and the ability to mentor engineers and partner with Finance and Audit leaders.

Build the data infrastructure, processing pipelines, curation strategies, and tooling that power frontier AI model training. The role requires strong distributed-data engineering experience and the ability to measure how data quality affects model outcomes.

Build and operate distributed web-crawling systems that source, extract, evaluate, and prepare large-scale web data for frontier AI models. The role requires hands-on crawler or scraping experience and strong distributed-systems engineering skills.

Senior Software Engineer building reliable connectors and high-volume data pipelines that move customer data into warehouses. The role requires strong Java, cloud, database, distributed-systems, and technical leadership experience.

Build and scale production data pipelines that transform raw healthcare and customer data into trusted canonical datasets powering ML models, dashboards, and product decisions. The role requires 6+ years of data engineering experience and strong Python, Spark SQL, and Airflow expertise.

Build and optimize foundational lakehouse infrastructure for AI, spanning metadata, transactions, table maintenance, storage layout, and query performance at massive scale. The role requires senior systems engineering experience with modern lakehouse technologies, columnar formats, cloud object storage, and systems-oriented programming languages.

Own and scale Mark43’s production database infrastructure, focusing on MySQL administration, monitoring, performance, reliability, upgrades, and recovery. The role requires at least seven years of production database experience, cloud infrastructure expertise, and familiarity with Terraform.

Lead the development and maintenance of scalable data pipelines, warehouse, and transformation layer using modern data stack. Collaborate with data scientists and analysts to ensure clean, reliable data for insights in a high-growth startup.

Leads the design and operation of highly available distributed data platforms and pipelines at Snowflake, while providing technical leadership across teams. Requires 12+ years of distributed-systems experience, cloud expertise, and strong database and system-design depth.

Build analytics data models, pipelines, dashboards, and AI-enabled automation for product and operational decision-making. The role requires 2–3+ years of data engineering or analytics experience, advanced SQL, dbt, cloud data warehouse, Python, and BI expertise.

Senior individual contributor responsible for architecting and scaling production data ingestion systems that integrate complex enterprise sources into reliable datasets. Requires 5+ years of backend engineering experience, strong Python, cloud, Kubernetes, Postgres, and data integration expertise.

Leads architecture and technical governance for an enterprise-scale data platform, driving distributed systems, data modeling, cloud infrastructure, and operational best practices. Requires 7+ years of engineering experience and a bachelor’s degree.

Analytics Engineer supporting Go-to-Market teams by building scalable data models, metrics, pipelines, visualizations, and self-service products. The role requires 10+ years of data experience, deep SQL expertise, Python proficiency, and strong business judgment.

Senior individual contributor who architects and builds end-to-end people data systems, predictive models, and AI-agent workflows. Requires 8+ years of experience across data engineering and data science, with expertise in Python, SQL, machine learning, sensitive HR data, and agentic AI.

Build and operate scalable data infrastructure, including partner data sharing, identity graph foundations, and governed batch and real-time platforms. The role requires 5+ years of data, distributed systems, infrastructure, or backend engineering experience and strong cloud and data-platform expertise.

Build data models, analyses, forecasts, automated dashboards, and AI-augmented analytics products for Finance and go-to-market operations. The role requires 2–4 years of analytical or analytics engineering experience, strong SQL and Python skills, and a quantitative degree.

Build and operate scalable enterprise data pipelines, models, and platform infrastructure across the full data lifecycle. The role requires 5+ years of experience, strong SQL and Python, and deep expertise in Snowflake, dbt, and Airflow.

Leads the architecture and hands-on development of a knowledge-graph-centered data platform for AI and autonomy workflows. The role requires deep distributed data systems expertise, strong Go or Python engineering skills, and experience with storage, APIs, infrastructure, and production reliability.

Staff Software Engineer on the central data platform team, responsible for architecture, ingestion, orchestration, streaming, governance, and self-service data tooling. Requires 10+ years building production data infrastructure and deep experience with warehouses, CDC, streaming, orchestration, Python, and SQL.

Leads the strategy, architecture, and development of large-scale data infrastructure powering big data and AI applications. Requires 10+ years of industry experience, deep expertise in Kubernetes and big data technologies, and proficiency in a programming language.

Own the reliability, performance, observability, scalability, and cost efficiency of large Aurora MySQL production environments supporting healthcare applications. The role requires 6+ years of database engineering experience, deep MySQL and AWS expertise, and strong skills in automation, incident response, and query optimization.

Build and lead the central data platform, covering ingestion, warehousing, orchestration, streaming, self-service frameworks, and trust layers. The role requires 5+ years of production data infrastructure experience, strong Python and SQL skills, and expertise with Snowflake and modern data tooling.

Own end-to-end data sourcing and vendor operations that help researchers train and evaluate frontier AI models. The role requires strong judgment, communication, problem-solving, and comfort managing ambiguous, fast-changing projects.

Builds production data systems, AWS infrastructure, artifact storage, edge-to-cloud pipelines, and ML infrastructure for robotics applications. Requires 2+ years of AWS data infrastructure experience, strong schema and data modeling skills, and experience with ML systems.

Leads organization-wide Snowflake migration, Medallion architecture, warehouse optimization, and CI/CD quality controls while partnering with executives on data strategy. The role requires 6+ years in analytics or data engineering, expert SQL, production dbt experience, and strong architectural judgment.

Leads multidisciplinary teams building production-grade data platforms, AI/ML systems, scientific computing environments, and modeling capabilities for biomedical research. The role requires at least eight years of technical experience, five years leading technical teams, and hands-on experience operating complex systems.

Build and maintain reliable data pipelines, warehouses, and lightweight data applications supporting analytics, operational models, and AI/ML workflows. The role requires SQL, Python, ETL, and data warehousing knowledge, with 1+ year of relevant experience preferred.

Leads architecture for offline experimentation and route simulation while building reliable, scalable data pipelines and backend services. The role requires 5+ years of backend or data engineering experience, distributed-systems expertise, strong SQL and Spark skills, and proficiency with modern cloud infrastructure.

Build and operate the streaming, storage, query, and self-service infrastructure underlying the company’s data platform. The role suits an early-career engineer with 1–3 years of experience, a computer science bachelor’s degree, programming skills, and interest in distributed systems.

Owns the Finance data infrastructure supporting billing, usage-based revenue, forecasting, reporting, and close. The role requires production data engineering experience, strong SQL and Python, dbt and orchestration expertise, Finance-domain fluency, and the ability to mentor engineers and partner with business stakeholders.

Owns end-to-end GTM data pipelines, transformations, and models that power reliable pipeline, revenue, attribution, and funnel reporting. The role requires senior-level data engineering experience, strong SQL and Python, dbt and orchestration expertise, GTM metric fluency, and stakeholder partnership skills.

Build and operate Databricks-based data products and pipelines that produce and distribute declared and modeled audience segments. The role requires strong Python, SQL, Spark, and distributed-processing expertise, plus experience with Databricks data engineering features and modern AI-assisted development.

Build and operate a scalable data platform centered on entity resolution, knowledge graphs, and real-time risk decisioning. The role requires strong software engineering, graph database, data pipeline, API, cloud, and observability experience.

Staff-level engineer leading backend services and data-platform architecture, including large-scale ingestion, distributed systems, and trustworthy BigQuery/dbt warehouse models. Requires 10+ years of software engineering experience, expert Python, deep SQL/dbt expertise, and strong technical leadership.

Senior Data Infrastructure Engineer responsible for building and operating reliable, low-latency streaming and batch data systems that support AI products. Requires 5+ years of production data infrastructure experience and expertise with technologies such as Kafka, Flink, ClickHouse, and Terraform.

Leads the migration and evolution of Vanta’s multi-tenant data platform, designing highly reliable ingestion, storage, and query systems at terabyte scale. The role requires staff-level distributed-systems expertise, Kafka and database fluency, and the ability to drive architecture across teams.

Build the data systems behind frontier coding models, spanning web crawling, large-scale pipelines, data quality models, and training-ready dataset infrastructure. The role requires strong distributed-systems or data-platform expertise and end-to-end ownership.

Provides technical leadership for Pinterest’s data warehouse foundation and agentic analytics platforms at massive scale. The role designs warehouse architecture, leads cross-functional initiatives, mentors engineers, and requires extensive data platform experience plus hands-on AI tooling expertise.