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Senior Data Engineer at Roblox builds and maintains scalable data pipelines, frameworks, and tooling to support analytics for a global 3D immersive platform, using cloud-based ETL orchestration tools and big data technologies.
Somos a Qeevo, um ecossistema de Aspiration Tech que conecta educação, evolução pessoal e consumo real. Nossos produtos impactam milhões de pessoas todos os anos, ajudando estudantes a encontrarem oportunidades…
Build and operate the MLOps platform for AI models that power a next-gen micromanufacturing compiler, handling training, deployment, serving, monitoring, and feedback loops.
Senior Data Engineer responsible for designing, maintaining, and scaling data pipelines for healthcare analytics, specializing in claims/membership data ingestion, Snowflake administration, and Dagster orchestration to support Medicaid patient management and cost reduction for primary care providers.
Build Python libraries and reproducible pipelines for analyzing imaging, ultrasound, and other scientific data to support brain-computer interface research.
About Ruggable: Ruggable is a leading direct-to-consumer e-commerce brand based in Los Angeles, California with an extraordinary track record of high, profitable growth. We pride ourselves on having an extremely loyal…
Build and operate the agent-first platform infrastructure that powers Snorkel AI’s products, including event-driven pipelines, governance systems, and distributed services using Python, AWS, and observability tools.
Designs and models scalable, interoperable data products for Oura’s health-focused platform using cloud data warehouses (Snowflake, BigQuery) and Data Mesh principles.
Leads the design and operation of a cloud-native data platform for a healthcare analytics company, focusing on scalable infrastructure, data pipelines, and AI/ML enablement.
Principal Data Engineer builds and leads a cloud-native data platform for a healthcare analytics company, designing scalable pipelines, governance frameworks, and AI/ML integrations while mentoring teams.
About Datavations Datavations is a leading New York-based data and AI software specializing in the $2.3 trillion dollar building materials industry. Datavations gives building materials and home improvement…
About Us SharkNinja is a global product design and technology company, with a diversified portfolio of 5-star rated lifestyle solutions that positively impact people’s lives in homes around the world. Powered by two…
About Formation Bio Formation Bio is a tech and AI driven pharma company differentiated by radically more efficient drug development. Advancements in AI and drug discovery are creating more candidate drugs than the…
Senior Data Analytics Engineer at VIA turns raw, sensitive customer data into trusted data products: owning ETL/ELT pipelines, building AI-powered analytics like anomaly detection and natural-language interfaces, and designing human-in-the-loop quality checks. Core stack includes Python/R, SQL/PostgreSQL, Dagster/Airflow/dbt, and AWS/Azure.
Senior Data Platform Engineer at VIA designs, provisions, and maintains cloud data infrastructure and resilient streaming/batch pipelines, while partnering with app teams on queries and pipeline reliability. Core stack: Python, SQL/NoSQL, AWS/Azure data services, Terraform/Helm, Kubernetes/Docker, Dagster/Airflow, and MLOps support.
VIA, a data-security software company, seeks a Data Analytics Engineer to turn complex customer data into trusted data products. Day to day: building ETL/ELT pipelines, AI-powered analytics and data quality checks using Python/R, SQL, AWS/Azure, and pipeline tools like Airflow and dbt. Hybrid role in Somerville, MA or Washington, DC.
Data engineer at Alfa-Bank building and maintaining ETL/ELT pipelines and analytical data marts for SME credit-risk reporting, integrating sources from DWH, operational databases, files and APIs. Core stack: SQL, Python, Spark, Airflow-class orchestration, analytical DBMS (Greenplum/ClickHouse/etc.) and Power BI/Tableau dashboards.
Data Engineer at Asian Pac Holdings in Kuala Lumpur, splitting time ~70% on data infrastructure (Airflow-orchestrated pipelines, Azure/AWS cloud, data lake/warehouse) and ~30% on applied AI (LangChain/CrewAI agents, RAG pipelines) supporting property-development analytics.
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