• Build, optimize, and maintain data pipelines into Palantir Foundry. • Integrate multiple healthcare data sources, including clinical, claims, supply chain, and other enterprise datasets. • Support rapid data onboarding to accelerate ontology development and population. • Design, build, and refine ontology objects, properties, relationships, and data mappings in Palantir Foundry. • Collaborate with business and technical stakeholders to translate requirements into scalable data and ontology structures. • Support ontology governance, versioning, and best practices. • Work across Pipeline Builder, Code Repositories, data integration workflows, and Foundry-based modeling efforts. • Contribute to a fast-moving implementation environment where rapid iteration and practical delivery are required.

Role Description As the Data Engineer you will be responsible for designing, building, and maintaining the data engineering function for a remote-first technology organization. This role oversees the full lifecycle of data architecture, pipelines, modeling, tooling, and reliability. It also involves operational duties and direct collaboration with technical leadership, including defining the complete data engineering strategy from the ground up. - Architect, implement, and maintain scalable data pipelines across core systems. - Build and manage analytics infrastructure using both open-source and commercial tools. - Ensure data quality and schema discipline for operational reliability. - Deliver clean, consistent models and dashboards utilized by multiple teams. - Collaborate with stakeholders to support analytics, business intelligence, and decision-making initiatives. Qualifications - 5+ years hands-on data engineering experience; big plus if you’ve been the first data hire before. - Strong SQL plus real programming ability (Python preferred). - Production experience with data tooling (Airflow, dbt, Fivetran). - Experience integrating APIs and working with warehouses/lakes such as Redshift, ClickHouse, or similar. - Experience with analytics/BI tools (Metabase, Looker, Tableau, PowerBI, etc.). - Comfortable with cloud infrastructure and IaC (AWS strongly preferred). - Soft skills to understand business needs and collaborate with non-tech teams on their use cases. - Embedded and real-time analytics experience is a plus. - Streaming architectures (Kinesis/Kafka), ClickHouse, ELK, VictoriaMetrics, reverse-ETL is a plus. Requirements - $5,000 - $7,000 USD/month - Unlimited PTO

Role Description As a Staff Software Engineer I on Data Delivery, you will lead complex technical initiatives across backend systems, with a focus on measurement and planning. You will act as a project and domain DRI for this area: - Translating product requirements into technical requirements - Clarifying feasibility and trade-offs - Shaping milestones and identifying risks - Keeping execution moving You will partner closely with product, engineering, and engineering management to recommend technical options, push back on unrealistic plans when needed, and help the team make sound decisions. Your work will help build the technical foundation for reliable customer-facing insights and make new product capabilities easier to launch and scale. What you’ll be doing - Domain ownership: Act as a project and domain DRI for measurement and planning initiatives within Data Delivery. - Technical planning: Translate product requirements into technical requirements, clarify feasibility and trade-offs, shape milestones, and identify risks early. - Execution leadership: Keep complex initiatives moving by unblocking decisions, coordinating across teams, and giving engineering leadership clear options and recommendations. - Scalable data systems: Build reliable systems that process, organize, and serve large volumes of campaign and marketing data across StackAdapt. - Customer-facing impact: Power reporting, measurement, planning, billing, pacing, exports, APIs, and analytics that customers and internal teams depend on. - System design: Make thoughtful technical decisions that balance correctness, reliability, latency, freshness, cost, and long-term maintainability. - Cross-functional partnership: Work closely with product, engineering, data science, analytics, and business teams to turn product goals into strong technical solutions. - Operational excellence: Improve monitoring, testing, data quality, incident response, and documentation so our systems are easier to trust and operate. - Technical mentorship: Support engineers through design reviews, code reviews, technical guidance, and clear communication of trade-offs. Qualifications - Backend and data systems experience: Strong experience building scalable services, distributed systems, data platforms, or data-intensive applications. - Project leadership: Experience leading complex technical projects with ambiguous requirements, multiple stakeholders, and meaningful trade-offs. - System design depth: Strong judgment across APIs, data pipelines, databases, distributed systems, observability, reliability, and operational ownership. - Data quality mindset: Ability to reason about correctness, freshness, completeness, consistency, cost efficiency, and customer trust. - Product judgment: Interest in building systems that support customer-facing reporting, measurement, planning, optimization, and analytics. - Technical communication: Ability to explain decisions clearly, align stakeholders, and document important trade-offs. - Mentorship: Experience helping other engineers grow and raising the technical bar of a team. - Technical stack: Strong programming skills; experience with Golang and technologies such as Kafka, TiDB, Redshift, Vitess, Iceberg, StarRocks, or Trino is a plus. - Domain experience: Experience in adtech, marketing technology, reporting, analytics, billing, attribution, planning, or high-volume event processing is a plus. What success looks like - Measurement and planning initiatives have clear technical direction, realistic milestones, and strong execution across teams. - Customers can trust the data they use to evaluate and optimize campaigns. - Core data systems are more reliable, scalable, and easier to build on. - New metrics, datasets, APIs, exports, and reporting capabilities can launch faster and with greater confidence. - Product and engineering teams can build new advertising, marketing, measurement, and AI-powered capabilities more easily. - The team makes better technical decisions because trade-offs are clearly understood and communicated. - Engineers around you grow through your mentorship, guidance, and example. - Data Delivery helps StackAdapt scale new product opportunities by giving customers a trusted view of performance across channels and the customer journey. Benefits - Highly competitive salary - Retirement/ 401K/ Pension Savings globally - Competitive Paid time off packages including birthday's off! - Access to a comprehensive mental health care program - Health benefits from day one of employment - Work from home reimbursements - Optional global WeWork membership for those who want a change from their home office and hubs in London and Toronto - Robust training and onboarding program - Coverage and support of personal development initiatives (conferences, courses, books etc) - Access to StackAdapt programmatic courses and certifications to support continuous learning - An awesome parental leave program - A friendly, welcoming, and supportive culture - Our social and team events!

Role Description Buscamos un(a) Arquitecto de Datos con más de 3-5 años de experiencia, responsable de definir la estrategia de arquitectura de datos de la organización, diseñar arquitecturas empresariales de alto nivel y liderar la implementación de soluciones de datos complejas, seguras, escalables y alineadas con los objetivos estratégicos del negocio. - Definir la estrategia de arquitectura y gobierno de datos de la organización. - Diseñar arquitecturas de datos empresariales y liderar su implementación. - Establecer estándares, lineamientos y mejores prácticas de arquitectura de datos. - Evaluar e incorporar nuevas tecnologías de datos. - Garantizar seguridad, calidad, capacidad, rendimiento y cumplimiento normativo. - Liderar iniciativas de Big Data, Data Warehousing, integración y calidad de datos. - Colaborar con líderes técnicos en la estrategia tecnológica corporativa. - Realizar análisis de impacto y definir evolución de la arquitectura de datos. - Impulsar innovación en datos, analítica, IA/ML y otras capacidades emergentes. - Liderar equipos y participar en reportes e iniciativas estratégicas. Qualifications - Más de 3-5 años de experiencia en arquitectura de datos. - Conocimiento profundo en arquitectura de datos empresariales, Big Data y Data Warehousing. - Experiencia en diseño de soluciones sobre AWS, Azure y GCP. - Conocimiento avanzado en seguridad de datos, cumplimiento normativo, calidad de datos, metadatos y datos maestros. - Experiencia en integración de datos compleja y entornos ágiles. - Conocimiento en arquitecturas de datos para IA/ML, IoT, Blockchain, serverless, edge computing y deseable computación cuántica. - Manejo de herramientas como TOGAF, Zachman, Snowflake, Databricks, Informatica PowerCenter, IBM InfoSphere, Collibra, Alation, Tableau Server, Power BI Premium, Imperva, Varonis, Informatica MDM, Profisee, Airflow y Control-M. Requirements - Liderazgo estratégico. - Visión de negocio. - Comunicación y negociación a nivel ejecutivo. - Influencia y capacidad de movilizar equipos. - Pensamiento crítico y resolución de problemas complejos. - Gestión de riesgos. - Innovación y creatividad.