Build, maintain, and operate data pipelines and curated data products across Snowflake, Airflow (MWAA), AWS, Python, and SQL.
Implement observability and data quality controls and build monitoring for freshness, volume, schema, distribution, and lineage.
Define and enforce data platform standards, establish orchestration patterns, DAG anti-patterns, deployment practices, observability standards, data quality patterns, and operational runbooks used across the organization.
Own and maintain data pipeline architectures, ensuring reliability and monitoring.
Manage and evolve data modeling environments for analysts and engineers.
Implement observability for data systems, detecting issues early and continuously monitoring data quality.
Voltus unlocks the full value of distributed energy resources for customers and the grid. They are a fast-growing climate-tech company with a bright, gritty, and good team that values innovation, impact, and integrity.
Build and maintain ELT pipelines using Fivetran and custom API integrations via Dagster, including setting up new source connectors and troubleshooting.
Manage and improve our Dagster orchestration — scheduling jobs, debugging failures, and keeping pipeline runtime tight.
Maintain and improve our GitHub Actions CI/CD workflows to ensure safe, reliable deployment of dbt models into production.
Wisp is on a mission to put healthcare back in patients’ hands by connecting them with hassle-free sexual + reproductive care online. They are a growing, fully-remote team in the United States looking for collaborators who are committed to their mission.
Build and optimize scalable data pipelines using Python and dbt.
Design and maintain Snowflake warehouse structures, database tables, and performant data models.
Develop reliable ETL/ELT workflows for extracting, transforming, loading, and validating data from multiple sources.
We are seeking a Senior Data Engineer to support core marketplace analytics data products and platform work. Enterprise experience is strongly preferred.
Build and Maintain Bronze/Silver Layer Pipelines: You will ensure core data sources lands accurately, on time, and with full lineage.
Lead Data Ingestion, Transformation, and Enrichment: You will own the end-to-end pipeline from raw file landing through cleansed, conformed staging tables, including deduplication, standardization, code mapping, and entity resolution.
Develop Automated Ingestion Pipelines: You will use Snowpipe, Matillion, or custom solutions with reliability, observability, and minimal manual intervention in mind.
Precision AQ is building a centralized Data Hub to consolidate fragmented data infrastructure, establish enterprise-wide data governance, and enable AI-ready analytics across our life sciences portfolio. This is a foundational initiative, not a maintenance role.
Lead and mentor a team of data engineers, ensuring best practices and high-quality deliverables.
Own and drive the end-to-end migration strategy from Snowflake on AWS to Azure Databricks and DBT.
Architect and oversee scalable, secure, and reliable data pipelines and infrastructure in Azure.
Coforge is a global digital services and solutions provider. They offer services in areas like cloud, data, and engineering. The company seems to have a culture of non-discrimination and hires based on skills.
Lead a team of data engineers, own the technical roadmap for our cloud data stack (Snowflake, Azure, dbt), and partner closely with stakeholders.
Establish and enforce organization-wide ETL/ELT best practices, naming conventions, and code review standards.
Magna Legal Services provides end-to-end legal support services to law firms, corporations, and governmental agencies throughout the nation. As an end-to-end service provider, they offer strategic advantages to their clients by offering legal support services at every stage of their legal proceedings.
Design, build, and maintain scalable data pipelines
Develop and optimize ETL processes to support data products
Work with structured and unstructured data across SQL and NoSQL systems
They are seeking a Data Engineer to support the development of data products that power critical business functions. They seem to have a collaborative, cross-functional Agile environment where you'll partner closely with technical and business teams to deliver high-quality data solutions.
Lead, coach, and develop a team of analytics engineers and/or data engineers.
Ensure on-time delivery of client data integrations by owning enterprise data model standards and maintaining consistent, governed data definitions.
Oversee client data pipelines using modern tooling (dbt, Airflow, Snowflake, AWS, Python) to ensure reliable operation and uptime.
SmarterDx builds clinical AI that is transforming how hospitals translate care into payment. Founded by physicians in 2020, their platform connects clinical context with revenue intelligence, helping health systems recover millions in missed revenue, improve quality scores, and appeal every denial.
Build and maintain data transformation pipelines with robust testing.
Design, implement, and maintain models with complex domain and business logic.
Optimize data storage and retrieval processes for improved performance and scalability.
Accorded is seeking experienced professionals to join their team. They are located in the San Francisco Bay Area, committed to creating a diverse and inclusive work environment and do not discriminate.
Design and implement batch and real time ingestion pipelines from internal and external sources.
Implement automated data quality checks, observability, and SLA monitoring.
Optimise datasets and pipelines for analytics, ML training, and API consumption.
Software Mind develops solutions that make an impact for companies around the globe. They build cross-functional engineering teams that take ownership and crave more, always on the lookout for talented people who bring passion and creativity to every project.
Engineer the Databricks platform across Azure and GCP.
Evolve data and AI governance in Unity Catalog.
Partner on data, feedback loops, and AI-driven data products.
Kinaxis is a global leader in modern supply chain orchestration, powering complex global supply chains and supporting the people who manage them. They have over 2000 employees around the world and they have a best-in-class HQ in Ottawa, Canada.
Build, maintain, and run CI/CD pipelines and infrastructure-as-code for the Smile Digital Health platform.
Provision, configure, and operate cloud-based Spark clusters and distributed data processing environments.
Design and maintain scalable, secure infrastructure templates and deployment automation across cloud environments.
Smile Digital Health makes it easy for healthcare stakeholders to collect and exchange data with our leading FHIR-based data liberation platform. At its heart, the Smile platform enables people and organizations to better manage healthcare data; the company was #19 on Deloitte's Technology Fast 50 Ranking for 2024!
Architect and evolve scalable data ingestion and egress frameworks and pipelines that are well tested and offer strong data quality monitoring.
Architect and evolve our CI/CD processes - enhancing the testing environment and observability.
Enhance our Claude Code / LLM development support capabilities - creating tools / skills / agents that give our LLMs more context and help us continually improve their abilities to debug, create code, and maintain systems.
Life360’s mission is to keep people close to the ones they love. They have a mobile app, tracking devices, and a pet GPS tracker. Life360 has more than 500 (and growing!) remote-first employees and delivers peace of mind and enhances everyday family life.
Development of various services in Python: integration with marketing partners, obtaining data from various sources.
Creation and support of processes on Airflow.
Supporting the migration of marketing data pipelines and DWH components from MS SQL to Google Cloud Platform (including BigQuery), contributing to architecture decisions and best practices.
Social Discovery Group (SDG) is one of the world's largest groups of social discovery companies, uniting millions of users on dozens of products. Our international team of 1000+ professionals and digital nomads works all over the world and we are proud to be a two-time “Great Place to Work” winner.
Work directly with business and technical stakeholders to identify high-value data and AI use cases that can be delivered on Databricks
Design, build, and deploy production-grade data and AI solutions using Databricks capabilities across the Lakehouse, Mosaic AI, Unity Catalog, Databricks SQL, Workflows, Delta Lake, Databricks Apps, Genie, Agents, and Lakebase
Lead client discovery sessions to understand business workflows, data availability, platform maturity, integration needs, and measurable success criteria
Aimpoint Digital is a market-leading data, AI, and operations research advisory and solution engineering firm. They help organizations build modern data platforms, enterprise AI systems, decision intelligence solutions, optimization models, and production analytics capabilities.
Design, build, and optimize integrations, automations, and AI-driven workflows that power our enterprise data and business operations.
Develop resilient data pipelines between core platforms (Salesforce, NetSuite, Snowflake, Slack).
Implement AI-enabled capabilities that reduce manual work and accelerate insights.
Tebra is an all-in-one EHR+ platform built exclusively for independent healthcare practices. They connect EHR software, billing, automation, telehealth solution, and marketing to streamline operations and reduce burnout, serving over 42,000 private practices.
Design, implement, and maintain a streaming-first data platform.
Build and operate a hybrid Databricks and Snowflake architecture.
Champion platform standards, tooling, and best practices across the data organization.
1Password is building a foundation for a safe, productive digital future to unleash employee productivity without compromising security. They have over 180,000 businesses trusting their teams; its culture prioritizes collaboration, clear communication, and alignment with core values.
Implement curated data model layer in dbt across data domains.
Design and build dbt models across the layered architecture.
Develop and optimize incremental models to handle high-volume domains.
Blend is an AI services provider, committed to co-creating meaningful impact for its clients through data science, AI, technology, and people. They aim to fuel bold visions by seamlessly aligning human expertise with artificial intelligence, dedicated to unlocking value and fostering innovation.
Instrument fal's core infrastructure to capture CPU, GPU, and request-level signals.
Build ingestion pipelines from partner APIs, compute vendors, and internal services into BigQuery.
Design and operate the ETL backbone that powers cost, margin, and usage analytics.
Fal is the generative media ecosystem powering the next generation of AI products. They build the infrastructure, tools, and model access that teams need to move from idea to production at scale.