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Designs and builds scalable ETL/ELT pipelines and data platforms using Spark and Airflow to deliver reliable data infrastructure and analytics for the business.
Design and maintain scalable ETL/ELT pipelines and data infrastructure using Apache Spark, Airflow, and Data Lake architectures to enable analytics and business decisions.
Maintains and optimizes Talend ETL/ELT pipelines for a 4-month on-site project, ensuring reliable data integration and resolving pipeline issues.
Senior Solutions Engineer partners with SI firms to architect and demo Snowflake-based data pipelines and solutions, leveraging PySpark, SQL, and cloud tooling to enable joint customer engagements.
Lead a global data engineering team to design, build, and maintain secure data platforms and pipelines using cloud (Azure/AWS/GCP), ETL/ELT, Kafka, and governance frameworks.
Data Transformation & Automation Engineer Position Summary As a GSC Data Transformation & Automation Engineer , you will play a critical role in enabling data-driven decision making across Global Supply Chain…
Builds and maintains ETL/ELT pipelines in Snowflake, cleans and models data, and writes SQL and Python code to transform raw information into analytics-ready datasets.
Designs and builds large-scale data pipelines and infrastructure to power AI/ML workloads and analytics for Amazon’s Device Operations in Mexico.
Builds modern ELT pipelines with dbt and Data Vault 2.0, runs Dagster workflows on OpenShift/Kubernetes, and processes streaming data with Kafka for near real-time analytics.
Build, migrate, and optimize data pipelines and ETL/ELT processes between SQL Server and Databricks, using T-SQL, Spark SQL, and PySpark to modernize legacy systems.
Builds and optimizes cloud data pipelines using T-SQL and Databricks, migrating legacy SQL Server workloads to scalable cloud infrastructure.
Design and build data pipelines and warehouses using Microsoft Fabric, Azure Synapse, and Power BI for enterprise clients, ensuring performance, governance, and security.
Designs and builds scalable ETL/ELT pipelines using Python and AWS services for cloud-based data warehouses.
Design and maintain scalable ETL/ELT pipelines in Python (PySpark) and Snowflake, optimizing data warehouses and ingesting data from REST APIs and cloud storage.
Lead a team building scalable Snowflake and AWS data pipelines for enterprise clients, enforcing Medallion Architecture, data quality, and governance in an ELT-focused environment.
Design and scale AWS-based data pipelines for high-volume time-series data from industrial sources, building a Data Lakehouse and optimizing ETL/ELT workflows for analytics-ready datasets.
Blendis a premier AI services provider, committed to co‑creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles…
Designs and maintains scalable data pipelines, warehouses, and governance frameworks using Python, SQL, and cloud tools to ensure clean, reliable data for analytics and reporting.
Senior Data Engineer builds and maintains scalable data pipelines and integrations in Azure, using Python, Kafka, Spark, and Databricks to process batch and real-time data for enterprise clients.
Designs and builds scalable ETL/ELT pipelines in the cloud, working with data science teams to enable reliable data workflows.
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