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Designs scalable data pipelines and architectures, builds ETL/ELT workflows, and optimizes SQL queries to support analytics and reporting in a cloud environment.
Data and Integration Engineer would be responsible for managing data and integration capabilities across WSP Digital Products, including structured, semi-structured, and unstructured data. The role would design and…
Designs and maintains mission-critical data infrastructure (Redshift, Aurora, pipelines) for Amazon’s Rest-of-World operations, optimizing performance, cost, and scalability while supporting 5K+ users and 70K+ daily jobs.
Builds and maintains scalable data pipelines and cloud-based data solutions for UK Defence programs, using Python, SQL, and Databricks in secure environments.
Lead a Databricks-based data platform team, designing scalable cloud architectures, mentoring engineers, and driving AI/data strategy with Spark, Delta Lake, and Python.
Build and maintain scalable Databricks pipelines and Lakehouse architectures using Spark, Delta Lake, and Python to deliver high-performance data products for a fast-growing tech business.
Build and maintain scalable data products using SQL, Snowflake, and Looker to deliver trusted datasets and BI reports for business stakeholders.
Builds and maintains scalable data pipelines to ingest, transform, and store data from diverse sources (relational, event-based, unstructured) for analytics, reporting, and AI/GenAI use cases, collaborating with business and IT teams to enable agile data delivery.
Build and maintain data pipelines and ELT workflows using Airflow, PySpark, Trino, and Snowflake to move and transform data reliably.
Build and maintain scalable data pipelines using Azure, Databricks, and Python to support enterprise reporting and analytics in a government-related financial institution.
Build and maintain scalable AWS data pipelines and lakehouse architectures for pharma analytics and AI/ML workloads, integrating commercial data sources like Veeva and Xponent.
Build and maintain ELT pipelines and data models on Databricks to power analytics and reporting for a cloud-based clinical system used by clinicians across the UK and France.
Builds and optimizes scalable data pipelines in PySpark and Databricks to power advanced analytics and AI initiatives for a global consulting firm.
Lead data engineering team to design scalable Snowflake-based pipelines, APIs, and AI integrations for logistics/construction data, optimizing performance and enabling analytics.
Builds and maintains scalable data pipelines for migrating/transforming financial data across systems, standardizing schemas, and enabling enterprise visibility into billions of dollars in payments. Core tech: Python/Scala/Java/C#, Databricks/Spark, cloud warehouses, ETL/ELT, and data quality tools.
Builds and maintains cloud-based data pipelines/AI solutions for healthcare analytics, collaborating with teams to optimize ETL/ELT workflows and ensure scalable, secure data platforms.
Build and optimize cloud-native data infrastructure and ETL/ELT pipelines using AWS, Python, and Terraform to support scalable healthcare applications.
Leads data engineering for a global healthcare company, designing scalable Oracle/PostgreSQL pipelines, optimizing performance, and mentoring teams to support mission-critical healthcare operations and analytics.
Build and maintain scalable data pipelines on Databricks using PySpark, Delta Lake, and cloud services to transform raw data into insights for analytics and AI workloads.
Designs and implements AI-driven architecture solutions, integrating GenAI/ML components into enterprise systems for fintech clients. Balances high-level design with rapid prototyping to validate ideas and align with business needs.
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