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Lead and build cloud data pipelines using Python, PySpark, SQL, and Databricks for enterprise banking systems, ensuring efficient ingestion, transformation, and analytics at scale.
Leads a team building scalable data platforms on Azure/AWS, using Spark, Hadoop, and Airflow to power enterprise analytics and AI solutions.
Lead a team to design and build data pipelines and warehouses for enterprise clients, using Python/Java/Scala, cloud platforms, and ETL tools.
Lead the design and build of cloud-native data platforms and AI-ready architectures at a major media company, setting standards and guiding multiple engineering teams.
Design and build scalable data platforms using Microsoft Fabric and Databricks, owning end-to-end pipelines and mentoring teams on delivery standards.
Lead a team building and optimizing an S3-backed OLAP data lake and ETL pipelines for a marketing analytics platform using Airflow and AWS.
Lead a team to design and maintain scalable OLAP pipelines on AWS, using Airflow for orchestration and S3-backed data lakes for marketing analytics.
Lead the design and delivery of Barclays' Enterprise Data Platform, focusing on data lineage and quality to ensure end-to-end visibility of data flows across a complex cloud ecosystem.
Lead the design and build of Attio’s scalable data infrastructure to power analytics and decision-making across teams.
Lead a team to design and build scalable data platforms for UK public-sector clients, using cloud services like AWS/Azure/GCP and technologies such as Apache Spark, Databricks, and IaC.
Lead a team building and scaling Azure-based data pipelines and AI-ready data models for a large ecommerce retailer using PySpark, Databricks, and Data Factory.
Lead the design and deployment of production-grade data pipelines and modern data platforms using Python, SQL, Snowflake, DataBricks, and cloud services to enable analytics and AI-driven decision making.
Lead AWS cloud engineering for a data platform that ingests third-party market data and powers AI/ML use cases across J.P. Morgan in an Agile environment.
Lead a team of data engineers to design and scale data platforms for analytics, building scalable pipelines and models in Databricks while driving governance and performance improvements.
Leads data-engineering projects for a culture-focused live-events platform, scoping solutions, gathering requirements, and coordinating delivery with engineers and product teams.
Lead the design and scaling of cloud-native data pipelines and AI-assisted engineering practices using Azure Data Factory, Databricks, Spark, and Python.
Lead a team building scalable data pipelines and solutions in Java and Azure Databricks, integrating cloud-native data workflows.
Lead a team to build automated BI pipelines and predictive analytics using Python, Databricks, SQL, and Tableau.
Senior Data Engineer builds and maintains secure, scalable AWS and Databricks data pipelines for JPMorganChase, leading projects and mentoring junior engineers while optimizing cloud costs.
Senior Data Engineer builds and maintains scalable ELT pipelines on Snowflake, AWS, and Airflow for a client, ensuring data quality and governance while advising on best practices.
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