21 of 21 Amazon EMR Jobs

Data ecosystems Hadoop, Spark, Kafka, Hive, HBase, etc. Strong experience with Cloud platforms (AWS/Azure/GCP) and services like: AWS: S3, Glue, EMR, Redshift, Lambda, Kinesis Azure: Data Factory, Synapse, Databricks, ADLS GCP: BigQuery, Dataflow, Pub/Sub Experience with Data Warehouse/Data Lake/Lakehouse

Data Engineer: Design, build and maintain scalable data pipelines and architectures within the AWS ecosystem Leverage services such as AWS Glue, Lambda, Redshift, EMR and S3 to support data ingestion, transformation and storage Work closely with data analysts, architects and business stakeholders to translate requirements into robust technical solutions

with at least one major cloud platform (AWS, Azure, or Google Cloud Expertise in cloud-native data services such as AWS Glue, Lambda, S3, EMR, Redshift, Lake Formation, Azure Synapse, Data Factory, Databricks, or BigQuery. Advanced knowledge of SQL, Python, Spark, PySpark, and distributed data frameworks. Proven background

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

pipeline, data warehouse and data lake design/building and data movement. AWS data and analytics services (or open-source equivalent) such as EMR, Glue, RedShift, Kinesis, Lambda, DynamoDB. What you can expect Work to agile best practices and cross-functionally with multiple teams and stakeholders.

pipeline, data warehouse and data lake design/building and data movement. AWS data and analytics services (or open-source equivalent) such as EMR, Glue, RedShift, Kinesis, Lambda, DynamoDB. What you can expect Work to agile best practices and cross-functionally with multiple teams and stakeholders.

scientists and analysts to ensure data quality, availability, and consistency for advanced modeling and reporting. Utilize AWS or other cloud services (e.g., S3, Glue, EMR, Snowflake) to architect and maintain cloud-based data ecosystems. Write and optimize complex SQL queries for data extraction, integrity checks, and performance tuning. Required

experience in data engineering or a similar role. • Hands-on experience with core AWS data services (for example S3, Glue, Athena, Lambda, IAM, EMR). • Strong SQL skills (joins, window functions, optimization). • Solid Python for data processing. • Experience building production ETL/ELT pipelines. • Working knowledge of security

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

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

/Tenable, etc.). Advantageous Security certifications such as AWS Security Specialty, AWS Solutions Architect, or equivalent. Experience supporting data platforms on AWS (Glue, EMR, Redshift, Athena, RDS, OpenSearch, Kafka/MSK). Knowledge of secure coding practices in Python/Node/Java or your core development stack.

follow AWS Well-Architected Framework principles (security, cost, performance, reliabilityData Engineering & Pipelines Build and optimize data pipelines in AWS using Glue, Lambda, Step Functions, EMR, Athena, and S3. Implement DAG-based orchestration using Apache Airflow, AWS Managed Workflows (MWAA), or Glue Workflows. Ensure data quality, reliability, lineage, and observability … patterns. Experience with CI/CD pipelines and DevOps on AWS.Preferred Qualifications AWS certifications (e.g., AWS Certified Data Analytics Specialty, Solutions Architect Experience with EMR, Redshift, Kinesis, or Kafka. Knowledge of MLOps tools (SageMaker, MLflow, Feature Stores Familiarity with IaC (Terraform, CloudFormation Experience working in enterprise-scale, highly regulated

experience in building data pipelines using Spark or Pandas. Experience with major cloud providers (AWS, Azure, or Google). Familiarity with big data platforms (EMR, Databricks, or DataProc). Knowledge of data platforms such as Data Lakes, Data Warehouses, or Data Meshes. Drive for self-improvement and eagerness

Experience building data pipelines using Spark or Pandas . Familiarity with major cloud platforms (AWS, Azure, or GCP). Understanding of big data tools (EMR, Databricks, DataProc). Knowledge of data architectures (Data Lakes, Warehouses, Mesh). A proactive mindset with a passion for learning new technologies. Nice

Building infrastructure and data architectures in Cloud Formation, and SAM. Designing and implementing data processing environments and integrations using AWS PaaS such as Glue, EMR, Sagemaker, Redshift, Aurora and Snowflake Building data processing and analytics pipelines as code, using Python, SQL, PySpark, spark, CloudFormation, lambda, step functions, Apache Airflow … Data Engineering role. Strong experience and knowledge of data architectures implemented in AWS using native AWS services such as S3, DataZone, Glue, EMR, Sagemaker, Aurora and Redshift. Experience administrating databases and data platforms Good coding discipline in terms of style, structure, versioning, documentation and unit tests Strong proficiency

Building infrastructure and data architectures in Cloud Formation, and SAM. Designing and implementing data processing environments and integrations using AWS PaaS such as Glue, EMR, Sagemaker, Redshift, Aurora and Snowflake Building data processing and analytics pipelines as code, using Python, SQL, PySpark, spark, CloudFormation, lambda, step functions, Apache Airflow … Data Engineering role. Strong experience and knowledge of data architectures implemented in AWS using native AWS services such as S3, DataZone, Glue, EMR, Sagemaker, Aurora and Redshift. Experience administrating databases and data platforms Good coding discipline in terms of style, structure, versioning, documentation and unit tests Strong proficiency

Your role will involve: Designing and developing scalable, testable data pipelines using Python and Apache Spark Orchestrating data workflows with AWS tools like Glue, EMR Serverless, Lambda, and S3 Applying modern software engineering practices: version control, CI/CD, modular design, and automated testing Contributing to the development … with or is eager to learn Apache Spark for large-scale data processing Is familiar with the AWS data stack (eg S3, Glue, Lambda, EMR) Enjoys learning the business context and working closely with stakeholders Works well in Agile teams and values collaboration over solo heroics

Frt. Lauderdale, FL. Candidates should be senior Data Engineers with big data tools (Hadoop, Spark, Kafka) as well as AWS (cloud services: EC2, EMR, RDS, Redshift) and NOSQL. This is a phone and Skype to hire. Candidates in Florida with a LinkedIn profile preferred but not required. Essential Duties … data tools: Hadoop, Spark, Kafka, etc. • Experience with relational SQL and NoSQL databases, including Postgres and Cassandra • Experience with AWS cloud services: EC2, EMR, RDS, Redshift • Experience with stream-processing systems: Storm, Spark-Streaming, etc. • Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.