Vagas remotas de Snowflake com elegibilidade clara.

Design, develop, and maintain scalable data pipelines and ETL/ELT workflows for structured and unstructured data.

• Senior
• AWS
• Azure
• CI/CD
• +4

Designs, builds, and maintains resilient ETL/ELT pipelines that ingest data from on‑premise systems, AWS services (S3, RDS), and Azure platforms (Blob Storage, Azure SQL)

• Senior
• AWS
• Azure
• Docker
• +3

Build advanced data pipelines utilizing the Medallion Architecture to create high-quality data sources in Snowflake.

• Senior
• AWS
• Azure
• GCP
• +3

Lead the end-to-end design, development, and implementation of enterprise data warehouse solutions supporting corporate analytics

• Senior
• CI/CD
• PostgreSQL
• Python
• +3

Design, develop, and optimize data pipelines and workflows for large-scale analytics and audience forecasting.

• Senior
• AWS
• Azure
• JavaScript
• +3

Design, implement, and optimize robust, scalable data pipelines using GCP services such as BigQuery, Cloud Dataflow, Cloud Dataproc, and Cloud Composer(or airflow).

• Senior
• GCP
• Java
• Python
• +2

Design, build, and maintain automated data pipelines that move data from source systems (Salesforce, Xero, Ramp, product databases) into our central data lake and warehouses

• Senior
• Python
• Salesforce
• Snowflake
• +1

Diseñar, desarrollar y mantenerpipelines de datos utilizandoAzure Data Factoryydbt.

• Middle
• Azure
• Snowflake

Design & Build Pipelines: Design, build, and maintain robust, scalable batch and streaming data processing, storage, and integration pipelines using technologies such as Apache Airflow or Benthos.

• Senior
• AWS
• CI/CD
• Docker
• +9

Pipeline Development: Design, build, and maintain data pipelines that ingest, transform, and deliver healthcare data (payer files, claims, attribution, eligibility) through staging, transformation, and mart layers.

• Senior
• CI/CD
• Python
• Snowflake
• +2

Build scalable ingestion and transformation with tests and documentation

• Middle
• Azure
• Python
• Snowflake
• +1

Bachelor's degree and 8+ years of technical experience in data engineering OR Master's degree and 4+ years of experience.

• Senior
• AWS
• Azure
• GCP
• +2

Design, develop, and deploy scalable and secure data pipelines and cloud-native architectures (data lakes, warehouses, and streaming pipelines) on AWS.

• Senior
• AWS
• CI/CD
• PostgreSQL
• +3

, and designing scalable data lake and data warehouse solutions. Experience across multiple data platforms (Databricks, Snowflake, Azure Data Factory, Synapse, etc.) is a strong advantage. Key Responsibilities 1.

• Senior
• AWS
• Azure
• CI/CD
• +5

(functional and non-functional) to develop scalable, automated, fault-tolerant data pipeline solutions for business and technology initiatives Profile data to assess the accuracy and completeness of data sources and work with business

• Middle
• AWS
• Azure
• CI/CD
• +3

Design & Build Pipelines: Design, build, and maintain robust, scalable batch and streaming data processing, storage, and integration pipelines.

• Middle
• AWS
• CI/CD
• Docker
• +7

Data Engineering & DevelopmentDevelop and maintain robust data integration pipelines (ETL and ELT) to process large volumes of financial data across cloud and on-premise environments.

• Senior
• AWS
• Azure
• CI/CD
• +3

Work in an Azure data warehouse environment, which includes developing database designs and architecture, data modeling and metadata repository creation

• Middle
• Azure
• Snowflake
• SQL

Build and operate pipelines: Design, build, and optimize robust ETL/ELT pipelines that move and transform millions of daily data points reliably and efficiently.

• Senior
• AWS
• Azure
• CI/CD
• +5

Design and build scalable, secure, and cost-effective data solutions in Snowflake.

• Senior
• AWS
• Azure
• GCP
• +3

You want to impact the industries that run our world: Your efforts will result in real-world impact—helping to keep the lights on, get food into grocery stores, reduce emissions, and most importantly

• Python
• Salesforce
• Snowflake
• +2

Design and implement tailored data solutions to meet customer needs and use cases, spanning from streaming to data lakes, analytics, and beyond within a dynamically evolving technical stack.

• Middle
• AWS
• Azure
• Java
• +2

Lead the full lifecycle of data engineering projects, from initial requirement gathering with stakeholders to production deployment and monitoring.

• Middle
• CI/CD
• Python
• Salesforce
• +2