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Designs and builds scalable big data pipelines using Spark, Hadoop, and Kafka to process large datasets for analytics and insights.
Build and maintain data pipelines and lakehouse layers for generative AI products using Python, SQL, and AWS tools like S3, Glue, and Redshift.
Design and maintain scalable data pipelines and ETL processes using Spark, Kafka, and Airflow, and optimize data storage in cloud warehouses and lakes to support analytics and ML initiatives.
Design and build a Flutter mobile app with a Java backend on AWS, leading architecture and integrations for a travel/proptech platform.
Build and maintain cloud infrastructure for a travel platform, automating deployments and CI/CD pipelines using AWS, Terraform, and Jenkins.
Build and maintain scalable data pipelines and lakehouse architectures to collect, process, and govern audio and vehicle telemetry for ML training and in-cabin personalization in automotive infotainment systems.
Build and maintain ETL pipelines in Python, Snowflake, and Airflow to ingest, transform, and deliver retail analytics data for financial use cases.
Build and maintain AWS-based ETL pipelines using Python, PySpark, Glue, Lambda, and Redshift to move and transform data for analytics.
QA engineer who designs and automates tests for Databricks data pipelines and cloud migrations on AWS/Azure, validating data accuracy and ETL logic.
Designs and maintains scalable data pipelines, warehouses, and governance frameworks using Python, SQL, and cloud tools to ensure clean, reliable data for analytics and reporting.
Lead a team to build and maintain ETL pipelines and a data lake for a marketing analytics platform using AWS S3, Airflow, and Athena.
Build and optimize cloud-native data pipelines and warehouses on AWS using Python, ETL/ELT tools, and modern data stacks for analytics and ML workloads.
Builds Databricks pipelines and migrates Redshift data to Databricks using AWS services like S3, Glue, and Athena.
Build and run Databricks pipelines and jobs to migrate data from Amazon Redshift, using AWS services like S3, Glue, and Athena while applying data governance practices.
Data Engineer to migrate a company’s data stack from Amazon Redshift to Databricks, building and running ETL pipelines while collaborating with stakeholders.
Build and maintain AWS-based data pipelines and ETL processes for a global financial data provider, using Python, Spark, and modern cloud tools to enable AI-ready analytics.
Build and maintain cloud-native data pipelines on AWS, landing data into Snowflake via dbt Cloud and Python, while optimizing performance and cost for analytics-ready datasets.
Build and maintain cloud-based data pipelines and warehouses for clients using AWS, SQL, and ETL tools like SnapLogic or Informatica.
Build and maintain AWS-based data pipelines and warehouses using Python, SQL, and services like Glue, Redshift, and S3 to enable analytics and ML feature stores.
Designs and builds AWS-based data pipelines and feature stores using Python, SQL, and tools like Glue and Sagemaker to support analytics and ML workloads.
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