Vagas remotas de SQL para candidatos em Estados Unidos.

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

Developing Python, SQL, and PySpark based applications and data flows in Databricks

• Senior
• Azure
• Python
• Spark
• +1

and delivery of robust and complete roadmap Assess data to determine strategic approach to data management and identify data dictionary Identify data security

• Senior
• Java
• Python
• SQL
• +4

Any experience with operational data science, machine learning or artificial intelligence solutions

• Senior
• Azure
• SQL

Design, develop, and maintain scalable data pipelines to ingest, transform, and curate logistics, maintenance, and supply chain data from multiple USMC systems.

• Middle
• AWS
• Azure
• CI/CD
• +3

Data Engineering & Pipeline DevelopmentDesign, develop, and maintain scalable ETL/ELT pipelines to support enterprise data integration and analytics.

• Middle
• Python
• REST
• SQL

, 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

Lead the design and implementation of complex data ingestion pipelines using PySpark, Databricks Intelligence Platform, and AWS services (S3, IAM roles and policies), including Kafka/streaming architectures, schema evolution

• Senior
• AWS
• CI/CD
• Python
• +2

Build and maintain data marts, materialized views, and data pipelines within an AWS Aurora PostgreSQL environment

• Middle
• AWS
• PostgreSQL
• SQL

Design, develop, and maintain scalable data pipelines.

• Senior
• Docker
• Kubernetes
• Python
• +2

Own Databricks production support for the Sugar Predict data platform, including monitoring, alerting, and incident response across all production data flows

• Senior
• AWS
• Azure
• CI/CD
• +4

Design, build, and maintain scalable data pipelines across diverse environments.

• Senior
• AWS
• Azure
• CI/CD
• +7

Partner with technical and non-technical stakeholders to translate business requirements into scalable, reliable, and maintainable data engineering solutions.

• Middle
• AWS
• Azure
• Python
• +2

Data platform architecture: ingestion patterns, warehouse design, environment strategy, orchestration, access governance, and reliability standards.

• Senior
• Azure
• CI/CD
• Snowflake
• +1

Regularly design, develop, and maintain data pipelines that support operational, analytical, and machine learning workloads

• Senior
• AWS
• Azure
• GCP
• +3

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

Build and maintain end-to-end pipelines in the Azure stack, ingesting source data into the Data Lake and Azure SQL, orchestrated with Azure Data Factory.

• Senior
• Azure
• SQL

Connect with cross-functional teams: The data environment we’re building will be used by members of the Accounting, Finance, Supply Chain, and Publishing teams, among others.

• Senior
• AWS
• Python
• SQL

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

• Middle
• Azure
• Snowflake
• SQL

Design, build, and maintain scalable data pipelines for analytics, ecommerce, logistics, and marketing.

• Senior
• AWS
• Docker
• Kubernetes
• +4

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, build, and maintain data pipelines and ETL/ELT processes supporting large-scale federal data systems

• Middle
• AWS
• Azure
• CI/CD
• +3

Build and maintain end-to-end Ingest → Transform → Expose pipelines using Airflow, Spark, dbt, and Iceberg.

• Middle
• AWS
• Python
• Spark
• +1