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Build and maintain robust ETL pipelines and cloud data infrastructure to ensure high-quality, reliable data flows for analytics and decision-making using AWS, Python, and modern data stack tools.
Build and maintain Feedzai’s data orchestration platform, integrating diverse data sources and enabling real-time fraud detection for banks and retailers using Java, Kafka, and cloud-native services.
Build and maintain AWS-based data pipelines and warehouses using Glue, Redshift, and S3, with CI/CD and IaC for scalable ETL/ELT workflows.
We are looking for an experienced Data Engineer (Cloud) to join our growing team. The ideal candidate should have hands-on expertise in designing and developing cloud-based data solutions using AWS, Databricks, Python,…
Design and build cloud-based data analytics infrastructure using AWS, Databricks, and IDMC, focusing on healthcare data pipelines and ETL/ELT workflows.
Lead a team to design and build Microsoft BI solutions (ETL, SSAS Tabular, Power BI) for banking domains, optimizing SQL Server performance and mentoring engineers.
Lead a team to build and maintain scalable ETL pipelines and cloud data platforms for government projects using AWS services like S3, Glue, and Redshift.
Architect and maintain scalable data pipelines and warehouses (Snowflake, Redshift, Athena) to power analytics and AI workflows, using Python, SQL, Airflow, and Kafka.
Lead a cloud-based data engineering team to build and maintain robust data pipelines, migrate legacy systems to Snowflake and AWS Glue, and ensure high-quality data flows for analytics and reporting.
Lead a small team to design, build, and scale data pipelines and platforms using Python, SQL, and cloud tools, ensuring reliable data for analytics and ML products.
Designs and maintains cloud data infrastructure on AWS and Databricks, building ETL pipelines and optimizing storage/processing for analytics using Python/Java/Scala.
Design and maintain scalable data pipelines, ETL/ELT processes, and cloud-based data warehouses using Spark, SQL, and cloud platforms like AWS/Azure/GCP.
Architect and maintain scalable data pipelines and cloud infrastructure to power analytics and AI-driven workflows using Snowflake, AWS Redshift, and Athena.
Build and optimize AWS-based data pipelines and Redshift warehouses for a government project, using Python, SQL, and DevOps practices to ensure secure, scalable data infrastructure.
Build and maintain AWS-based data pipelines and cloud infrastructure for Singapore’s legal sector, consolidating datasets and preparing data for AI-powered tools like LLMs.
Build and own a new HR data warehouse, then transition into analytics to help HR teams make data-driven workforce decisions using SQL, Python, and cloud pipelines.
Leads AI data engineering at a Singapore government agency, designing scalable data pipelines and governance for AI systems that support national security.
Build and optimize Plaud’s data platform to power AI-driven productivity tools, focusing on data warehousing, ETL/ELT, governance, and cloud services.
Build AI-ready data pipelines and knowledge systems for an investment firm’s agentic AI, integrating structured financial data, unstructured research, and real-time feeds into vector stores, graph databases, and retrieval pipelines.
Designs and builds cloud data pipelines on AWS and Databricks, architecting storage solutions and optimizing ETL workflows for analytics and reporting.
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