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Staff Software Engineer builds and scales data pipelines, APIs, and integrations for EnergyHub’s energy-grid platform, using Snowflake, AWS, gRPC, and Python to process billions of utility and DER data points.
Principal Data Engineer builds scalable pipelines and systems to ingest and process IoT device telemetry and utility data, enabling cleaner energy grids and virtual power plants using Python, SQL, Snowflake, and cloud tools.
Full-stack software developer building cloud-native enterprise applications for Nakisa's HR, financial, and real estate platform used by Fortune 1000 companies. Day to day: design and build backend services in Java/Spring Boot plus frontend components (Vue.js), optimize APIs and database schemas, and ship in an Agile, TDD team with AI-assisted tooling.
Build and maintain scalable data pipelines and metrics for DoorDash’s logistics operations, partnering with engineers and analysts to deliver trusted, self-serve analytics using SQL, Python, and tools like Snowflake and Tableau.
Build and scale data pipelines, ETL workflows, and warehouse models to power analytics and reporting at DoorDash.
Build and maintain data pipelines, models, and dashboards in Snowflake and Looker to power analytics for Wolt’s global delivery platform.
Senior Data Scientist focusing on Workforce Management Analytics at Wolt, building forecasting models, time series analysis, and optimizing resource allocation for operational efficiency.
About the Team DoorDash is a data driven organization and relies on timely, accurate and reliable data to drive many business and product decisions. Data is at the foundation of DoorDash success. The Data Engineering…
Build and scale data pipelines, warehouses, and models to power analytics and reporting at DoorDash, using Python/Java, Spark, Kafka, Airflow, and cloud data platforms.
Builds and maintains DoorDash’s scalable data platform (Spark, Flink, Kafka, Airflow) to enable real-time analytics, data governance, and business insights for logistics/delivery operations.
Build and scale high-performance data pipelines and warehouse models to power analytics and reporting at DoorDash, using Python/Java, Spark, Airflow, Kafka, and Snowflake.
Designs and maintains data pipelines and BI systems for DoorDash, integrating SevenRooms data and building AI infrastructure to support company-wide decision-making using tools like DBT, Looker, BigQuery, and Python.
Build and deploy ML models for delivery ETAs, prep-time prediction, and logistics optimization at DoorDash Drive, using deep learning, reinforcement learning, and multimodal AI.
Personetics, a fintech company building AI-driven 'Cognitive Banking' tools for banks, is hiring a Data Engineer in Giv'atayim (Tel Aviv District) to design and scale its BI data platform — owning ETL/ELT batch and streaming pipelines, data modeling, and governance using tools like Airflow, Databricks, Kafka, Python, SQL, and Power BI.
Alliance Especializados del Aire S.A de C.V. is seeking a Design Engineer to develop, validate, and improve HVAC unit designs for data center applications. You will create detailed engineering documents and support…
Senior Python data engineer at 3Pillar building a data and cloud migration framework that moves on-premise assets to Snowflake and Azure. Day to day: migrate databases and stored procedures, containerize and run workloads on Kubernetes/Docker in AKS, and uphold data engineering best practices within Agile teams.
Data Analyst Engineer at Hitachi Rail in Mexico City who builds and maintains ETL pipelines, runs statistical and predictive analysis, and creates dashboards (Tableau/Power BI) to turn complex data into business insights. Core stack: SQL, Python/R, Apache Airflow, cloud data platforms.
Senior data engineer at hiberus designing and building batch, streaming, and near-real-time pipelines plus lakehouse/data warehouse platforms on cloud (AWS, Azure, or GCP), centered on Snowflake, advanced SQL, and Python, while partnering with BI, analytics, and business teams.
Hands-on Technical Director building data platforms and AI infrastructure (LLMs, RAG) using Python, AWS, and vector databases.
Build and maintain ML infrastructure for autonomous military systems, including data management, model training/orchestration, and edge deployment pipelines using Python, PyTorch, and Kubernetes.
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