Leads enterprise data engineering strategy, architecture, delivery, governance, and technical leadership across the organization. Requires extensive data engineering experience, advanced data modeling and warehouse expertise, and strong PySpark, SQL, and Python skills.

Staff Software Engineer leading development of data catalog and metadata infrastructure for discovery, governance, lineage, and quality across Airbnb’s data ecosystem. Requires 9+ years of software engineering experience focused on data infrastructure and strong programming and distributed data technology skills.

Leads the design, operation, and technical direction of Pinterest’s data workflow and context control planes, driving reliability, scalability, AI-native capabilities, and open-source contributions. Requires 10+ years of distributed-systems experience, infrastructure expertise, and proficiency in Python or Java.

Staff Software Engineer building scalable frameworks for high-performance financial data ingestion/distribution and AI-native products. Requires 7+ years experience with distributed systems, microservices, and data architectures; partners with product teams to drive technical direction.

Build and operate scalable lakehouse infrastructure, streaming and CDC pipelines, query systems, and self-serve BI capabilities. Requires 5+ years of data engineering experience, strong Kubernetes and infrastructure-as-code expertise, and hands-on experience with distributed data platforms.

Leads database architecture, performance, reliability, and developer-tooling initiatives for high-volume trading applications. Requires 8+ years of software engineering experience, expert MySQL skills, backend development expertise, and strong knowledge of distributed systems and database operations.

Own the company’s metric governance program by defining canonical metrics, enforcing them in semantic and catalog systems, improving data quality, and validating AI-agent outputs. Requires 5+ years in analytics or analytics engineering, strong SQL, production semantic-layer ownership, and experience with AI evaluation and data governance.

Build and operate distributed systems powering Apache Pinot’s real-time analytics platform at massive scale. The role requires strong distributed-systems expertise, end-to-end delivery ownership, and a focus on reliability, observability, and performance.

Own and scale transformation pipelines that convert diverse financial and operational data into reliable FP&A-ready models. The role requires strong SQL and dbt expertise, data integrity and performance skills, and effective collaboration across Engineering and Customer Success.

Build and operate low-latency systems that capture, normalize, and distribute real-time market data for institutional trading. The role requires backend engineering experience, Java or C++, market data infrastructure knowledge, and exchange connectivity expertise.

Architects and builds ZoomInfo’s distributed data-platform infrastructure, including federated GraphQL access, real-time pipelines, indexing, and observability. The role requires 10+ years of software engineering experience, cloud-native expertise, and strong distributed-systems design skills.

Leads the strategy, architecture, and scaling of Pinterest’s big data and AI infrastructure across petabyte-scale workloads. Requires principal-level technical leadership, extensive Kubernetes or big data platform experience, and proficiency in modern data and cloud technologies.

Staff-level engineer responsible for the technical direction, reliability, and evolution of a cloud ELT platform supporting healthcare data products. The role requires 7+ years of software or data engineering experience, deep SQL/Python and modern data-platform expertise, and strong architectural and mentoring leadership.

Build scalable analytics engineering infrastructure, SaaS data models, and AI-enabled workflows that support enterprise decision-making. The role requires 3–6 years of hands-on analytics or data engineering experience, strong SQL and modern data modeling expertise, and cloud data warehouse experience.

Senior data engineer who will set architecture standards, lead large-scale pipeline initiatives, and build reliable cloud-native data platforms on AWS. The role requires expertise in orchestration, batch and streaming systems, infrastructure as code, and modern data architectures.

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.

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.

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.

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.

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.

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 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.

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 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.

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.

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.

Leads the re-platforming of Vanta’s compliance data layer from MongoDB to schema-aware PostgreSQL across high-throughput Kafka and S3 pipelines. The role requires staff-level distributed systems expertise, migration leadership, and strong experience with relational and document data modeling.

Build and scale AWS-based data infrastructure, pipelines, knowledge graphs, and APIs for a CTV performance advertising platform. The role requires production data engineering experience with Spark, Scala, AWS, SQL, and large-scale services, plus a bachelor's degree.

Leads the strategy, architecture, and hands-on development of scalable AWS data ingestion and transformation platforms. Requires expert Python and SQL skills, Terraform and cloud-native pipeline experience, and 8+ years in data engineering or backend development, with technical leadership responsibilities.

The Senior Analytics Engineer will architect and operate marketing data infrastructure, productionize predictive models, and enable attribution, experimentation, and customer activation. The role requires strong Snowflake, dbt, Python, SQL, and Segment expertise, plus experience with marketing data and cross-functional analytics initiatives.

Own the systems that ingest, standardize, validate, and operationalize data signals for Vanta’s EPD organization. The role suits a hands-on builder who has recently shipped working tools or pipelines, uses AI-assisted development, and helps teammates grow technically.

Build and operate distributed data applications powering large-scale audience segmentation and real-time personalization. The role requires 2–4 years of software engineering experience, backend development skills, and familiarity with databases, algorithms, and distributed systems.

Leads an analytics engineering team that transforms raw data into reliable, actionable insights for product, marketing, and operations. The role requires 7+ years in data or analytics engineering, management experience, and advanced SQL, Databricks, and dbt expertise.

This staff-level data engineer will architect and operate low-latency market data infrastructure, including feed handling, normalization, distribution, and exchange connectivity. The role requires at least five years of backend engineering experience and strong Java or C++ expertise with high-throughput messaging and market data protocols.

Leads the analytics engineering function, owning data architecture, modeling standards, semantic layers, governance, and roadmap execution while managing and developing the team. The role requires deep SQL and dbt expertise, dimensional modeling experience, cloud data warehouse knowledge, and strong senior-stakeholder communication.

Architects scalable data systems and platforms using distributed technologies like Spark, Kafka, and AWS. Mentors engineers and drives innovation on large-scale data projects, requiring 8+ years experience and expertise in data infrastructure.

Own and evolve Bevi’s end-to-end data platform, from ingestion and IoT modeling through governed self-service analytics and AI access. The senior individual contributor will architect scalable streaming and batch systems, establish governance and observability, and provide technical leadership across the Data & Data Science organization.

Builds agentic AI, automated data workflows, and BI solutions for complex telecommunications datasets. The role requires 5+ years of technical data and automation experience, strong SQL and Python skills, and expertise in data governance and LLM-based tools.

The Senior Data and AI Specialist will build agentic AI solutions, automated Python workflows, and analytics products across telecommunications data. The role requires at least five years of experience with SQL, data automation, BI tools, LLM agents, and data governance.

Leads the design and delivery of scalable data infrastructure, services, and developer tooling while shaping technical direction and mentoring engineers. Requires 8+ years of software engineering experience, strong systems design expertise, and proficiency in a modern programming language.

Owns marketing-sourced pipeline across multiple growth motions by designing, launching, and optimizing integrated B2B SaaS campaigns. The role requires 10+ years in demand generation or growth marketing, pipeline ownership, strong funnel analytics, and hands-on experience with Salesforce, Marketo, and ABM platforms.

Builds customer intelligence workflows that turn product usage, engagement, and contract data into actionable insights for Customer Success. The role requires strong Python and SQL skills, a bachelor's degree, and an interest in applied AI, automation, and predictive customer health modeling.