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Build and maintain secure, compliant big-data pipelines on AWS, using Python, PySpark, and Terraform to provision analytics-ready datasets for enterprise reporting and governance.
Senior Data QA Engineer at Abacus Insights ensures healthcare data accuracy and compliance for a cloud-native platform, designing automated validation frameworks and mentoring teams using SQL, Python, Java, and AWS/Databricks.
Leads architecture and engineering for an AI data engine that accelerates ML dataset generation and warehouse operations for autonomous-vehicle models, using cloud infrastructure and agentic AI workflows.
Build and maintain scalable Azure-based data pipelines and warehouses using Python, SQL, and modern data engineering practices to enable AI-driven analytics for global enterprise clients.
Builds and maintains BigData ETL/ELT pipelines in Python/Java, moving data from APIs, logs and databases into DWH and Data Lake using Spark, Airflow and Hadoop tooling.
Build and maintain scalable data pipelines and lakehouse architecture on Databricks and AWS to power fintech products used by millions across Southeast Asia.
Own commercial analytics for a global fintech/ecommerce platform, building trusted metrics and dashboards in dbt, Tableau, and Looker to drive revenue, margin, and risk decisions.
Designs and leads enterprise-scale Customer Data Platform (CDP) architectures, integrating MarTech ecosystems like Adobe AEP/AJO, Braze, and Salesforce, with a focus on AI-driven personalization and data governance.
Build and maintain a Python/PySpark-based data pipeline engine on AWS and Azure, automate CI/CD with GitHub Actions, and develop AI agents for configuration and troubleshooting in a global healthcare biopharma company.
Build and deploy ML models end-to-end: train, optimize, and package solutions while setting up MLOps pipelines, monitoring, and data governance for production AI systems.
The team you will join designs, develops, and deploys innovative enterprise technology and AI-driven tools to support the delivery of tax services. It is a dynamic group combining expertise in tax, software…
Build and maintain data pipelines and warehouses using Microsoft tools, migrating legacy SAS logic into modern SQL-based solutions for trusted analytics and reporting.
Build and scale real-time, globally distributed data pipelines and identity graphs for an adtech platform using Python, Spark, and cloud infrastructure.
Staff Software Engineer in the Realtime & Streaming team at Judi Health, responsible for designing, building, and operating streaming infrastructure including WAL replication and event streaming platforms. The role involves leading batch-to-streaming migrations, setting technical standards, and ensuring timely event delivery across various data consumers.
Build and prototype AI-driven algorithms for fraud detection and AML compliance using large financial datasets, Scala/Python, Spark, and Kafka.
Build and maintain Tookitaki's cloud-native platform on AWS EKS using GitOps (Argo), Terraform, and Kubernetes operators, enabling self-service infrastructure for application teams.
Build and maintain production data pipelines on Databricks, transforming raw data into clean, governed datasets for analytics and AI teams using PySpark, SQL, and Delta Lake.
Principal Data Engineer builds and scales real-time and batch data pipelines using PySpark, Kafka, Flink, and cloud orchestration tools, while leading a team and mentoring peers.
Designs and maintains scalable data pipelines on Databricks and Azure Synapse using PySpark, Python, and SQL to enable reliable analytics and AI workflows.
Build and run a cloud-based data lakehouse platform for a fintech client, automating deployments, monitoring performance, and optimizing queries with tools like Dremio, Spark, and Terraform.
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