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Build and maintain ETL/ELT data pipelines on AWS (S3, Redshift, QuickSight) using Python, PySpark, SQL, and tools like Talend, Power BI, Pentaho, SSIS, and Azure Data Factory.
Data Engineer designing and building scalable ETL/ELT pipelines for large-scale customer and financial data migrations using SQL, Python, and AWS, working remotely from Spain.
The Senior Azure Data Engineer will design and maintain scalable cloud-based data platforms, pipelines, and warehouses using Azure services, Databricks, and PySpark. This remote role supports energy sector operations and requires extensive experience in data engineering and SQL development.
Senior Data Engineer on a 3–4 month contract designing and maintaining ETL/ELT pipelines on Microsoft Fabric Lakehouse, implementing medallion architecture (bronze/silver/gold layers) with SQL, Python, and Spark.
Taligent is seeking a Semi-Senior Data Engineer to design and maintain scalable cloud data pipelines for analytics and AI. The role involves working with heterogeneous data sources and developing APIs to support predictive models and visualization tools.
Design and operate production-grade ETL/ELT pipelines integrating data from APIs, databases, SaaS, and cloud services while ensuring data quality and governance across hybrid environments using AWS/Azure data tools, CI/CD, and IaC.
The Snowflake Data Engineer will build and maintain cloud-native data ingestion and ELT pipelines on AWS and Snowflake. The role involves collaborating with cross-functional teams to develop and deploy production-ready data solutions and dimensional models.
Data engineer building pipelines, ETL/ELT flows, and semantic layers for an Enterprise Datahub using Databricks, SQL, and BI tools.
The Data Engineer will design, build, and maintain scalable ETL/ELT pipelines and data platforms to support business intelligence and machine learning initiatives. The role requires proficiency in SQL, Python, and ETL tools to ensure data integrity and system performance.
Senior data engineer designing and running production-grade ETL/ELT pipelines with PySpark, managing a lakehouse architecture across raw/curated/consumption layers, and deploying with Kubernetes and Docker in on-prem environments.
Transform raw data into reliable datasets and Looker dashboards using dbt, SQL, and data modeling on cloud platforms, partnering with analysts and engineers to optimize ELT processes.
The Cloud Data Engineer will build and maintain data infrastructure for campaign planning and reporting using GCP, BigQuery, Looker, and Salesforce. This role involves developing ETL/ELT pipelines and integrating APIs within a media and marketing environment.
This Data Engineer role involves building and maintaining data infrastructure for marketing and advertising campaigns using GCP, BigQuery, Looker, and Salesforce. The position is a 3-day-per-week onsite contract based in Central London.
Responsibilities The Reporting & Data Analytics platform underpins regulatory reporting, risk visibility, member reporting and internal analytics across SwapClear and Listed Rates Given the scale, criticality and…
Data Engineer building ELT pipelines, data models, and analytics solutions using Python, Databricks, AWS, and SQL at JPMorgan Chase in London.
Data Engineer owning the Atlas CDP build, working on event streaming, identity resolution, Snowflake warehousing, and dbt transformations with production-grade ETL/ELT pipelines.
Design and maintain cloud-based data platforms and data warehouse solutions, building ETL/ELT pipelines with Databricks, Spark, SQL and Python while automating deployments via Terraform and CI/CD pipelines in an Azure environment.
Hands-on Data Engineer building scalable analytics and AI-enabled data solutions on Snowflake and Azure using Python, dbt, and CI/CD for an asset management firm.
DevOps Engineer at a London-based psychological science startup, owning cloud infrastructure, CI/CD pipelines, and observability while supporting AI/ML workloads on AWS.
Design and implement enterprise data platforms on Databricks, build ETL/ELT pipelines with Spark/PySpark/SQL, and provide technical leadership for data architecture and legacy migration projects.
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