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GCP Data Engineer at TCS building and maintaining GCP-based big data pipelines (batch and realtime) using BigQuery, Airflow, Dataflow, DataProc, and Python/PySpark across India.
Senior Cloud & AI Architect providing technical leadership for cloud-native, microservices-based, and AI-enabled platforms for a Federal Government entity, focusing on Kubernetes/OpenShift, DevSecOps, and AI engineering.
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 scalable data pipelines and ETL/ELT solutions on GCP using DBT, Terraform, SQL, and large-scale processing frameworks like Spark/Beam/Hive.
Big Data Engineer responsible for developing and optimizing queries using Hadoop, HIVE, PySpark, and Spark SQL within a big data ecosystem.
Senior Data Engineer designing and maintaining real-time and batch data pipelines for SMC Global Securities' financial services and trading platforms, using SQL, Python, AWS (S3, Redshift, Athena, Glue, EMR, Lambda), Airflow, DBT, and Spark within Data Lakehouse architectures.
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.
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.
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.
Senior Data Engineer building secure, automated, scalable GCP data pipelines using Python, Apache Airflow, Apache Druid, and Spark for a global ad-tech DSP platform.
Lead/Senior Data Engineer designing and delivering scalable data pipelines and platforms using Python, Scala, Spark, and SQL, while mentoring a team and collaborating cross-functionally.
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.
Build and maintain scalable data pipelines using Spark, Scala, Airflow, and Azure Databricks in a hybrid role based in Bengaluru. Work with modern data lakehouse technologies, containerization, and CI/CD practices.
Senior Data Engineer building and operating production-grade data pipelines on AWS (S3, Glue, EMR, Redshift, Lambda) using Python and SQL, with Airflow, Delta Lake, and streaming tools, for a political/policy research analytics firm in Bangalore (hybrid).
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.
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.
Mid-Level Big Data Engineer with 4-6 years of experience building and supporting large-scale Big Data applications and cloud-based data pipelines using Python, AWS EMR, Spark, SQL, and AWS cloud services with focus on EMR performance tuning and cost optimization.
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.
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