1 to 25 of 58 Amazon EMR Jobs

Commercial experience in client-facing projects is a plus, especially within multi-disciplinary teams Deep knowledge of database technologies: Distributed systems (e.g., Spark, Hadoop, EMR) RDBMS (e.g., SQL Server, Oracle, PostgreSQL, MySQL) NoSQL (e.g., MongoDB, Cassandra, DynamoDB, Neo4j) Solid understanding of software engineering best practices - code reviews, testing frameworks ...

data solutions that meet complex business needs and support informed decision-making. Experience Required: Strong AWS expertise, including tools such as Glue, Lambda, Kinesis, EMR, Athena, DynamoDB, CloudWatch, SNS and Step Functions. Skilled in modern programming, particularly Python, Java, Scala and PySpark. Solid knowledge of data storage ...

data solutions that meet complex business needs and support informed decision-making. Experience Required: Strong AWS expertise, including tools such as Glue, Lambda, Kinesis, EMR, Athena, DynamoDB, CloudWatch, SNS and Step Functions. Skilled in modern programming, particularly Python, Java, Scala and PySpark. Solid knowledge of data storage ...

role Excellent knowledge of data modelling, warehousing concepts, and large-scale distributed systems Hands-on experience with cloud-based data tools (AWS Redshift, Glue, EMR or similar) Proficiency in Python and SQL Understanding of DevOps principles, including CI/CD and IaC (e.g. Terraform) Clear communication skills ...

data systems. Proficiency in Python, Java, or Scala - comfortable writing robust, testable, and scalable code. Deep experience with AWS (Lambda, ECS/EKS, EMR, Step Functions, S3, IAM, etc.). Strong knowledge of distributed systems and streaming/data pipelines (Kafka, Spark, Delta, Airflow, etc.). Familiarity with infrastructure ...

years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud) 5+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL) 4+ year experience working on real-time data and streaming applications 4+ years of experience with NoSQL implementation (Mongo ...

years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud) 4+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL) 4+ year experience working on real-time data and streaming applications 4+ years of experience with NoSQL implementation (Mongo ...

years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud) 4+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL) 4+ year experience working on real-time data and streaming applications 4+ years of experience with NoSQL implementation (Mongo ...

/BSS workflows. Key Responsibilities 1. Data Engineering & ETL Development Design, develop, and maintain ETL/ELT pipelines using AWS-native services (Glue, Lambda, EMR, Step Functions). Implement data ingestion from telecom systems like OSS/BSS, CDRs, mediation systems, CRM, billing, network logs . Optimize ETL workflows … Iceberg Implement and maintain Apache Iceberg tables on AWS for schema evolution and ACID operations. Build Iceberg-based ingestion and transformation pipelines using Glue, EMR, or Spark. Ensure high performance for petabyte-scale telecom datasets (CDRs, tower logs, subscriber activity). 4. Querying & Analytics (Athena) Develop and optimize Athena ...

wide range of AWS services (e.g., EC2, S3, RDS, Lambda, IAM, VPC, CloudFormation, DynamoDB) Skilled in AWS analytics tools (Glue, Athena, Redshift, EMR, Kinesis, MSK, QuickSight, dbt) Understanding of information security best practices Strong verbal and written communication in English and local language Ability to lead ...

wide range of AWS services (e.g., EC2, S3, RDS, Lambda, IAM, VPC, CloudFormation, DynamoDB) Skilled in AWS analytics tools (Glue, Athena, Redshift, EMR, Kinesis, MSK, QuickSight, dbt) Understanding of information security best practices Strong verbal and written communication in English and local language Ability to lead ...

Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...