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The Senior Manager of Data Engineering will lead a team to design and maintain scalable ETL/ELT pipelines and data warehouse models. The role focuses on technical strategy, data governance, and cross-functional collaboration using Python, SQL, and cloud-based data platforms.
The Senior Analytics Engineer will build and optimize data pipelines using dbt, Airflow, and ELT practices while developing Power BI dashboards. The role requires extensive experience in data modeling and Snowflake to support analytics and reporting.
The Analytics Engineer will build and maintain data pipelines using dbt, Python, and Airflow while developing Power BI dashboards and data models. The role requires extensive experience in SQL, cloud data warehousing, and dimensional modeling to support business reporting and data quality.
The Data Platform Engineer will design and build production-grade data pipelines and systems to support analytics and AI initiatives. The role involves managing core platforms like Snowflake, dbt, and Dagster while driving data reliability and self-service tooling for the organization.
The Data Engineer will develop and maintain secure ETL/ELT pipelines to prepare and structure data for AI and RAG workflows. The role emphasizes data quality, governance, and compliant access controls.
The Senior Data Engineer will design and maintain scalable data pipelines, ETL/ELT processes, and lakehouse architectures on Azure to support healthcare analytics. The role requires expertise in Python, SQL, and big data technologies like Spark and Kafka to ensure high-performance data processing and compliance.
The Data Engineer will build and maintain secure ETL/ELT pipelines to prepare data for AI solutions, focusing on data quality, integration, and governance. The role requires 3-5 years of experience with SQL, Python, and enterprise system integrations.
Data Engineer at ALL IN GROUP (an e-commerce company) in Munich, owning and developing the data warehouse platform, building ETL/ELT pipelines using Python, SQL, GCP, BigQuery, dbt, SQLMesh, and Airbyte.
Builds and maintains scalable data pipelines, ETL/ELT processes, and cloud-based data solutions for an energy company’s modern data platform, ensuring reliability, performance, and cross-functional collaboration.
Senior Data Engineer building ELT pipelines, SQL transformations, and Snowflake data models to deliver AI-ready datasets, supporting SAP MM procurement processes and S/4HANA migration.
ETL/ELT consultant for a strategic decision-support system, focused on analyzing requirements, modeling, and populating datamarts using Semarchy xDI and SQL.
Data Engineer designing and developing ETL/ELT pipelines, setting up data warehouses and lakes, and maintaining data infrastructure using Kafka, DBT, Spark, Snowflake, GCP, Azure, Kubernetes, and Airflow.
Data Engineer building Big Data pipelines, streaming solutions, and Datalake/NoSQL environments using Apache Spark, Kafka, and Databricks at a European parcel delivery leader.
Build data architectures and ETL/ELT pipelines using Python, SQL, and Spark at Sogeti's Aix-en-Provence office, collaborating with business and IT teams.
Builds and maintains data pipelines, warehouses, and lakes; designs data architectures; ensures data quality and reliability for business use cases using Python, SQL, and cloud platforms.
Build and maintain global data pipelines from raw sources to curated layers, ensuring quality and performance for analytics and data science teams.
Designs and builds data pipelines (ETL/ELT) while setting up data storage/treatment solutions (warehouses, lakes) to ensure long-term data infrastructure reliability for analytics and AI teams.
Builds and maintains Databricks-based data pipelines to integrate structured/unstructured data, designs data models, and enables AI/analytics use cases by ensuring high-quality, governed data for business processes and applications.
Data Engineer building a central Databricks-based data platform with an AI focus—designing data pipelines, modeling data structures, and developing data products using SQL, Python, and ETL/ELT processes.
Design, develop, and maintain ETL/ELT data integration pipelines on a Corporate Data Platform using SQL, Python, Spark, Databricks, and cloud services, collecting and transforming data from business and manufacturing systems.
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