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Data Engineer designing and building ETL/ELT processes on Azure using SQL and Python for a global IT services firm.
DevOps engineer deploys and maintains Kubernetes clusters, automates CI/CD pipelines, and sets up monitoring for AI and data services using Terraform, GitLab CI, ArgoCD, Prometheus, and Grafana.
Design and implement an end-to-end AWS Data Lake and Lakehouse solution, define standards, govern metadata, and build scalable ingestion pipelines using AWS services, SQL, and Python or Scala.
Design and lead cloud-native data platform and Data Lakehouse initiatives for a government housing agency, building scalable data architectures, ETL/ELT pipelines, and multi-cloud migration strategies.
The Senior Data Engineer will design and maintain scalable cloud-native data pipelines and Data Lakehouse architectures to support evidence-based decision-making. The role involves leveraging modern data engineering tools like Python, SQL, Spark, and Kafka while implementing infrastructure as code and MLOps practices.
Design and build data integration pipelines into EPM/CPM solutions using Microsoft Fabric and Azure Data Stack, ingesting data from SAP, Workday, and other source systems, implementing Lakehouse architectures, and validating data quality in a fully remote role.
This Senior BI Developer role involves designing and implementing modern data solutions using Microsoft Fabric, Power BI, and Azure. The position focuses on building data pipelines and warehouses while integrating AI-driven applications, automation, and agents into client projects.
The Senior Data Engineer will design and maintain scalable ETL/ELT pipelines within a Databricks Lakehouse environment to support BI and AI initiatives. This hybrid role requires expertise in Python, SQL, and Azure cloud services, emphasizing software engineering best practices like CI/CD and Infrastructure as Code.
Senior Data Engineer building scalable data pipelines and platform components on the Databricks Lakehouse using SQL, Python, and PySpark, with IaC and CI/CD practices for analytics and AI use cases.
The Data Engineer II will design and maintain scalable data pipelines, warehouses, and lakes to support analytics, AI, and automation initiatives. The role requires proficiency in SQL, Python, and cloud platforms to build reliable, governed data foundations.
Manage Databricks infrastructure and implement CI/CD pipelines with security and governance compliance on AWS Government Commercial Cloud (GCC) for the MSF DataSphere data lakehouse platform.
The DevOps Engineer will manage and optimize Databricks infrastructure within an AWS Government Commercial Cloud environment. The role focuses on implementing CI/CD pipelines, ensuring strict security compliance, and supporting data lakehouse operations.
Design and build streaming and batch data pipelines on AWS (Kafka, Spark/Flink, S3 lakehouse) for Pirelli's manufacturing Data Platform, transitioning legacy systems to a data-driven architecture while supporting global production plants.
Data Engineer III building and maintaining cloud-based data pipelines, lakehouse architectures, and analytics solutions on AWS (S3, Glue, EKS, Lambda) using Python and Spark for JPMorgan's International Consumer Bank.
Principal Data Engineer leading the Azure lakehouse data platform (Fabric, Databricks, Data Lake) for Scottish Water—setting technical standards, reviewing PRs, designing scalable data pipelines, and collaborating across analytics, data science, and architecture teams.
Principal Azure Data Engineer leading cloud data platform engineering at Scottish Water, designing data pipelines and lakehouse architectures on Azure while collaborating with data scientists and platform teams.
Data Engineer building and owning the data lakehouse behind a flight optimization engine at Jeppesen ForeFlight in Odense, focusing on data quality at ingestion, training dataset creation, and scalable batch pipelines on AWS using Python and SQL.
Data & AI Engineer designing and scaling backend services, APIs, databases, and cloud-native solutions to support RWE Offshore Wind's engineering and renewable energy operations, using Python, Azure, Databricks, Docker/Kubernetes, and AI/LLM frameworks.
Data & AI Engineer designing and scaling backend applications, databases, APIs and cloud-native solutions for RWE Offshore Wind's Engineering department, using Python, Azure, Databricks and LLM-based AI tooling.
Data Engineer building and owning an Iceberg/S3 data lakehouse for flight recorder data ingestion, quality validation, and savings reporting to optimize airline fuel efficiency.
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