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Build and own scalable ETL pipelines and data warehouses for a hospitality workforce-management SaaS, using AWS Glue, Airflow, Spark, and modern lakehouse formats.
Build and scale data pipelines, event streaming, and AI-powered analytics for Just Eat’s retail media platform using BigQuery, dbt, Airflow, and GCP/AWS.
Build and maintain scalable data pipelines and GenAI platforms on AWS using Spark, Iceberg, and Bedrock to power analytics, AI, and RAG systems for a fintech-focused company.
Design and build scalable payment data models and cloud-native ELT pipelines for a fintech platform handling cards, ACH, wallets, and cash payments.
Build and optimize AWS-based ETL pipelines using Glue, PySpark, and EMR Serverless to migrate and transform large datasets for a tech-sector client.
Build and optimize AWS Glue/PySpark ETL pipelines for large-scale data migration and transformation, enforce technical standards, and review code in a cloud-native data platform.
Build and maintain scalable data pipelines and GenAI platforms on AWS using Spark, Iceberg, and Bedrock to power analytics, AI, and RAG systems.
Build and optimize scalable data pipelines and lakehouse infrastructure (Spark, Databricks, Snowflake) for a SaaS data-management platform, and help kick-start early AI use cases.
Senior Data Engineer modernizes a large bank’s Big Data platforms, migrating batch jobs to Cloudera CDP and Google Cloud using Spark, SQL, and Kubernetes while ensuring performance and reliability.
Build and maintain robust data pipelines and ETL workflows for a public-sector client using Talend/Informatica, Airflow, and modern data platforms like Trino and Iceberg.
Build and maintain robust data pipelines (ETL/ELT) on cloud platforms, ensuring data quality, security, and governance while collaborating with data scientists and analysts.
Build resilient data pipelines and self-serve tooling for a crypto market maker, normalizing market, trading, and portfolio data in real time for desks, risk, finance, and research.
Build and optimize scalable data pipelines and lakehouse infrastructure (Spark, Databricks, Snowflake) for a SaaS data-management platform, with early AI use-case enablement.
Build and scale ML infrastructure for a quantitative trading firm, designing feature stores, MLOps pipelines, and data lakes to support petabyte-scale time-series models in low-latency environments.
Build and maintain a cloud-based pathogen genomics data platform using Python, Airflow, and Oracle/AWS/Azure to ingest, process, and secure genomic and clinical data for early epidemic warnings and diagnostics.
Build and maintain large-scale data pipelines and curated datasets for a modern Lakehouse and AI data platform, using Python, SQL, Spark and Snowflake to support analytics and AI use cases at a global bank.
Lead the development of a global enterprise platform using Java, Spring Boot, and AWS, designing APIs, databases, and event-driven services for Universal Music Group’s internal teams.
Lead the design and delivery of cloud-native data services for Citi’s strategic platform, migrating to Databricks and building scalable Spark/Scala solutions on AWS to power global finance operations.
Lead a team engineering cloud-native data services for Citi’s strategic platform, migrating to Databricks and building scalable Spark/Scala solutions on AWS to power global finance systems.
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