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Design, build, and optimize scalable data pipelines and cloud data platforms on AWS using Python, PySpark, and services like Glue, EMR, S3, Redshift, and Athena.
Director leading a Data & AI practice—combining executive leadership, solution architecture, pre-sales consulting, and delivery oversight across AI/ML, Generative AI, analytics, and cloud platforms (AWS, Azure, GCP).
Evaluate AI-generated data engineering implementations—ETL/ELT pipelines, data warehouses, distributed systems—using frontier AI coding agents, with Python and SQL as core technologies.
Build and maintain data pipelines, storage (including vector databases), and a metrics layer to power AI agents for customer support data, using big data tools, Python/PySpark, and cloud data warehouses.
AWS Data Engineer designing data strategies, building big data solutions on AWS/Spark/Hadoop, programming in Scala/Python/Java/SQL, and tuning Spark for billion-record processing.
Design, develop, and maintain GCP data pipelines and data warehousing solutions using BigQuery, Dataflow, Cloud Composer, and Cloud Storage while ensuring data governance and cost optimization.
Big Data Engineer responsible for developing and optimizing queries using Hadoop, HIVE, PySpark, and Spark SQL within a big data ecosystem.
Design and develop real-time data pipelines and scalable data processing solutions on AWS using Kafka, Spark, and AWS Kinesis.
The Senior Data Solutions and Cloud Architect/Engineer will design and manage scalable cloud-based data environments on Azure to support advanced analytics and business decision-making. The role involves leading technical teams, building data pipelines, and ensuring compliance with security and GxP standards within a MedTech environment.
Senior Data Engineer building real-time data ingestion/processing pipelines and large-scale enterprise data solutions using PySpark, Python, Airflow, SQL, and AWS big data services.
Lead and hands-on build data & analytics solutions using Databricks, Informatica, and Tableau on AWS for Eisai's global pharmaceutical data platform, driving BI, AI, and data democratization.
Hands-on Technical Lead / Senior Data Engineer leading an offshore BAU Data Engineering team, maintaining and improving GCP data pipelines with a focus on BigQuery, Cloud Composer/Airflow, Python, and SQL production support.
Senior Data Engineer building data pipelines and ETL workflows on AWS and Databricks, working with big data technologies like Spark, Snowflake, and Airflow in a media-domain context.
AWS Data Engineer at TCS responsible for designing, building, and optimizing scalable data pipelines and analytics solutions on AWS using services like Glue, S3, EMR, Redshift, Databricks, and PySpark.
GCP Data Engineer role focused on building and maintaining data pipeline architecture, data warehouse modernization, and cloud-based data lakes using Google Cloud Platform big data technologies and PySpark.
Lead Data Engineer building data pipelines for analytics and data science use cases on Big Data platforms, primarily using Spark, Scala, Hadoop, and Hive.
Lead Data Engineer designing and developing scalable batch and streaming data pipelines using Apache Spark, PySpark, and Databricks, with data modeling and integration responsibilities to support BI and analytics tools.
Lead a team of data architects and engineers, owning end-to-end solution architecture for AB InBev's global data platform using Azure/AWS big data stack, Spark, SQL, and containerized microservices.
Design and build data pipelines, warehouses, and predictive analytics models for supply chain data using Python, Java, SQL, Spark, Hadoop, and Azure/AWS cloud platforms at a Life Sciences/Healthcare consultancy.
Senior Data Engineer building scalable data platforms on Azure using Scala and Spark, handling data ingestion, transformation, and analytics enablement for a digital transformation consultancy.
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