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ML Engineer building generative AI/ML models and driving data modeling activities for a life-sciences customer engagement platform, using Python, PySpark, Databricks, and cloud computing.
The Senior Azure Data Engineer designs and implements large-scale data engineering solutions using the Azure stack, including ADF, Databricks, and Synapse. The role requires extensive experience in Python, SQL, and Spark within an agile and DevOps-driven environment.
Designs and oversees large-scale data and AI architectures, balancing latency, cost, and scalability for Michelin’s enterprise systems. Focuses on Lakehouse (Delta Lake/ADLS Gen2), ML pipelines (Azure ML/AKS), and data models (PostgreSQL/Snowflake) while ensuring security and compliance.
The Scrum Master/Release Train Engineer will manage Agile ceremonies and program execution for DoD data and AI initiatives using Palantir Foundry. The role involves coaching technical teams, tracking sprints, and aligning program objectives with federal mission requirements.
Azure AI Data Architect designing and implementing enterprise-scale data platforms and AI/GenAI solutions on Microsoft Azure, partnering with stakeholders across client engagements at a global consultancy.
Roles & responsibilities The Manager/Lead Data Engineer will be part of the GDC CRC team, working in a technical leadership role within the Audit Data & Analytics domain. The role requires expertise in data…
Design and build scalable batch and streaming data pipelines using Python, SQL, Pyspark, and Databricks for a car-financing company, ensuring data quality, observability, and alignment with business needs.
This role involves developing secure, scalable data engineering solutions for a global KYC and risk assessment platform using Python, PySpark, and cloud-native technologies. The engineer will lead architectural decisions, mentor team members, and implement data-intensive applications within an agile environment.
Designs and optimizes large-scale data platforms and AI/ML architectures using Databricks, Spark, Delta Lake, and Unity Catalog, ensuring scalability, security, and performance across cloud environments.
Builds and maintains data models/transformations for analytics, optimizing performance for Power BI/Microsoft Fabric dashboards in an insurance client’s decision-making environment.
Develops and optimizes Power BI reports for hospitality and commercial reporting, focusing on hands-on execution and performance improvements using DAX and semantic modeling.
Principal Consultant - Lead Data Analyst / Data Modeller Company: Transform Together Contract: 6-month Fixed Term Contract, with option to extend or become a permanent member of the team Compensation: OTE £90,000…
Data Architect - Greater Manchester (Hybrid) - Up to £80,000 We're working with a highly successful, private equity-backed organisation that is undergoing a major data transformation programme and investing heavily…
Data Architect (Microsoft Fabric) | UK Remote/Hybrid | £100,000 - £120,000 Peaple Talent have partnered with a leading data consultancy that's continuing to invest heavily in its Data & AI practice and is…
Job Advertisement: Senior Data Scientist Location: Welwyn Garden City Contract Type: Fixed Term Contract Contract Length: 12 months (6+6) Daily Rate: £550 - £800 per day Inside IR35 Working Pattern: Hybrid About the…
Experienced Senior Data Engineer to work on a focused migration project — converting existing Scala-based Spark pipelines to PySpark and transitioning job workloads from classic Databricks clusters to Databricks…
Leads a team building and maintaining enterprise data pipelines, data products, and canonical data models to support analytics, AI, and reporting, ensuring scalable, reliable, and high-quality data solutions.
Builds and optimizes a marketing analytics platform by integrating pharmaceutical data sources into Power BI, ensuring data quality and automation for business insights.
The Data Engineer designs and maintains scalable data pipelines and marts within a Databricks Lakehouse on Azure. The role focuses on data quality, governance, and collaboration with analytics teams to deliver reliable data products.
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