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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.
Senior Data Engineer working on-site in Bengaluru or Hyderabad, building ETL/ELT pipelines and data warehouses using AWS services (Glue, EMR, Redshift, S3, Athena) with Python, PySpark, and SQL.
Data Engineer designing, developing, and maintaining scalable ETL/ELT pipelines, data warehouses, and data lakes using SQL, Python, and Big Data technologies (Spark, Databricks) on Azure/cloud platforms for an Azure-focused managed services company.
Design, develop, and optimize large-scale data processing solutions and high-performance data pipelines using Spark, Scala, and the Hadoop ecosystem for distributed analytics platforms.
Data Engineer at a consulting firm designing and building scalable, cloud-native Big Data and analytics platforms using Azure, Databricks, Spark, and Python for enterprise clients.
Big Data Engineer designing, developing, and optimizing scalable data pipelines using PySpark, Hadoop ecosystem tools (HDFS, Hive, Sqoop), SQL/HiveQL, and workflow orchestration via Airflow or Oozie.
An AWS Data Engineer designing and implementing big data solutions, tuning Spark for high-volume data processing, and troubleshooting performance issues.
Data Engineer designing and building data pipelines, ETL/ELT processes, and data models using Azure Data Factory, SQL, and big data technologies to support analytics and business insights.
Build and maintain scalable ETL/ELT data pipelines and optimize data infrastructure using Python, SQL, and big data technologies like Spark, Kafka, and cloud data warehouses.
Experienced Data Engineer joining a regulatory banking data squad to design, develop, and maintain Spark-based ETL pipelines (batch and streaming) on a Cloudera/Hadoop environment, with 3 days on-site in Vannes.
Design and implement Master Data Management solutions for a global fintech leader, ensuring data consistency and governance across enterprise systems like Reltio and Salesforce.
Lead data science projects at a leading Indian credit card issuer, building AI/ML models for credit and fraud risk, and creating dashboards to turn data into business insights.
Develops and maintains Java-based enterprise applications using Spring, Kafka, and big data tools like Hadoop, with a focus on scalable, distributed systems in Singapore.
Lead IT and Infosec audits for a leading Indian credit-card issuer, designing analytics models in Python/R to surface risks and drive corrective actions across the IT landscape.
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