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Core qualifications Bachelor's degree in Computer Science, IT, Engineering, or a related field with a demonstrated continuous learning ethos. Minimum 10 years of hands-on experience in the design, development, and…
Build scalable data pipelines and ETL workflows in Python and Spark, then deliver insights via dashboards in Power BI or Looker for a healthcare-focused product team.
Senior Data Engineer builds and optimizes large-scale data pipelines using Spark, Python, and AWS for a major UK organization’s AI estate.
Builds and optimizes large-scale data pipelines and AI-driven workflows in a complex enterprise environment using Spark/PySpark, Python, and AWS, with hands-on engineering focus.
Designs, builds, and optimizes data pipelines on Databricks and AWS to power UK healthcare systems, ensuring scalability, security, and compliance with NHS standards.
Builds and maintains data pipelines and analytics platforms using Microsoft Fabric, Delta Lake, and Azure technologies to transform enterprise data into actionable insights for reporting and decision-making.
Designs and maintains large-scale data pipelines using Databricks, PySpark, and Azure Data Factory to modernize enterprise data infrastructure, ensuring governance, security, and performance for analytics.
L3 support engineer troubleshooting and optimizing Databricks, Airflow, and DBT workflows to maintain enterprise data platform reliability, performance, and stability.
Develops and optimizes data platforms and ELT pipelines on Databricks Lakehouse, using SQL, Python, PySpark, and Delta Lake to integrate data sources and deliver consulting solutions from design to production.
Develops and optimizes Databricks Lakehouse-based data platforms and ELT pipelines, implementing data models (Data Vault, 3NF, dimensional) and integrating diverse data sources while advising clients on technical architecture and deployment processes.
Designs and implements scalable data architectures using Databricks (Delta Lake, Unity Catalog) to solve complex data challenges for clients in healthcare, finance, and government. Leads technical teams, mentors engineers, and drives cloud-native data solutions with Python/Java and modern data workflows.
Builds and maintains FATCA/CRS/PTR regulatory reporting pipelines using Python, PySpark, SQL, and AWS to ensure accurate, traceable, and on-time data delivery in a cloud environment.
Designs and maintains cloud-native data platforms using SQL/data warehousing, Spark/PySpark, Databricks, Kafka, and Airflow for enterprise-scale data pipelines.
Builds and optimizes data pipelines in Azure/Databricks for clients, focusing on ETL/ELT, lakehouse solutions, and orchestration while bridging technical and business needs in a consulting environment.
Designs, builds, and operates cloud-native data platforms using Python, Spark, Kafka, and modern cloud tools (GCP/AWS/Azure) while applying software engineering best practices to solve business problems through scalable data pipelines and analytics.
Senior Data Engineer builds and optimizes PySpark ETL pipelines and ML scoring models to improve contact data accuracy for millions of business professionals, working with AWS services and medallion lake architecture.
Builds and maintains data pipelines in Azure Lakehouse, transforms raw financial data into BI-ready models, and creates Power BI dashboards for a fintech client.
Designs and maintains scalable data pipelines and lakehouse architectures using Databricks and PySpark for analytics and AI/ML workloads.
Builds and maintains data pipelines, lakehouse infrastructure, and BI tools for a Malaysian fintech firm, using Azure PaaS, Power BI, and Python/SQL to transform raw data into actionable insights for end users.
Build and maintain scalable data pipelines and Lakehouse solutions using Databricks and PySpark, ensuring high-performance analytics and governance for enterprise reporting and AI/ML workloads.
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