1 to 25 of 169 Amazon EMR Jobs

and Kinesis. Work with structured and unstructured data from multiple sources, ensuring efficient data ingestion, transformation, and storage. Develop and optimize data lake and data warehouse solutions using Amazon S3, Redshift, Athena, and Lake Formation. Implement data governance, security, and compliance best practices, including IAM roles, encryption, and access controls. Monitor and optimize performance of data workflows using … a strong focus on AWS cloud technologies. Proficiency in Python, PySpark, SQL, and AWS Glue for ETL development. Hands-on experience with AWS data services, including Redshift, Athena, Glue, EMR, and Kinesis. Strong knowledge of data modeling, warehousing, and schema design. Experience with event-driven architectures, streaming data, and real-time processing using Kafka or Kinesis. Expertise in IaC More ❯

Full-time | Hybrid | London | Up to £95,000 + Bonus & Excellent Benefits | Key Responsibilities: Design, develop, and implement advanced data pipelines and ETL/ELT workflows using cloud-native services such as AWS Glue, Lambda, S3, Redshift, and EMR. Act More ❯

Drive the design development and implementation of complex data pipelines and ETL/ELT processes using cloud-native technologies (e.g. AWS Glue AWS Lambda AWS S3 AWS Redshift AWS EMR). Develop and maintain data quality checks data validation rules and data lineage documentation. Collaborate with data analysts data scientists business stakeholders and product owners to understand their data More ❯

Drive the design development and implementation of complex data pipelines and ETL/ELT processes using cloud-native technologies (e.g. AWS Glue AWS Lambda AWS S3 AWS Redshift AWS EMR). Develop and maintain data quality checks data validation rules and data lineage documentation. Collaborate with data analysts data scientists business stakeholders and product owners to understand their data More ❯

Drive the design development and implementation of complex data pipelines and ETL/ELT processes using cloud-native technologies (e.g. AWS Glue AWS Lambda AWS S3 AWS Redshift AWS EMR). Develop and maintain data quality checks data validation rules and data lineage documentation. Collaborate with data analysts data scientists business stakeholders and product owners to understand their data More ❯

Drive the design development and implementation of complex data pipelines and ETL/ELT processes using cloud-native technologies (e.g. AWS Glue AWS Lambda AWS S3 AWS Redshift AWS EMR). Develop and maintain data quality checks data validation rules and data lineage documentation. Collaborate with data analysts data scientists business stakeholders and product owners to understand their data More ❯

role with advanced experience in at least most of the following technologies Cloud Platforms: AWS (Amazon Web Services): Knowledge of services like S3, EC2, Lambda, RDS, Redshift, EMR, SageMaker, Glue, and Kinesis. Azure: Proficiency in services like Azure Blob Storage, Azure Data Lake, VMs, Azure Functions, Azure SQL Database, HDInsight, and Azure Machine Learning Studio. Data Storage … Azure Purview. Data Security Tools: AWS Key Management Service (KMS), Azure Key Vault. Data Analytics & BI: Visualization Tools: Tableau, Power BI, Looker, and Grafana. Analytics Services: AWS Athena, Amazon QuickSight, Azure Stream Analytics. Development & Collaboration Tools: Version Control: Git (and platforms like GitHub, GitLab). CI/CD Tools: Jenkins, Travis CI, AWS CodePipeline, Azure DevOps. Other Key More ❯

buy online. By giving customers more of what they want - low prices, vast selection, and convenience - continues to grow and evolve as a world-class e-commerce platform. Amazon's evolution from Web site to e-commerce partner to development platform is driven by the spirit of innovation that is part of the company's DNA. The world … come to to research and develop technology that improves the lives of shoppers and sellers around the world. About Team The RBS team is an integral part of Amazon online product lifecycle and buying operations. The team is designed to ensure Amazon remains competitive in the online retail space with the best price, wide selection and … good product information. The team's primary role is to create and enhance retail selection on the worldwide Amazon online catalog. The tasks handled by this group have a direct impact on customer buying decisions and online user experience. Overview of the role: A candidate will be a self-starter who is passionate about discovering and solving complicated More ❯

data processing) Apache Spark Streaming, Kafka or similar (for real-time data streaming) Experience using data tools in at least one cloud service - AWS, Azure or GCP (e.g. S3, EMR, Redshift, Glue, Azure Data Factory, Databricks, BigQuery, Dataflow, Dataproc Would you like to join us as we work hard, have fun and make history? Apply for this job indicates More ❯

data processing) Apache Spark Streaming, Kafka or similar (for real-time data streaming) Experience using data tools in at least one cloud service - AWS, Azure or GCP (e.g. S3, EMR, Redshift, Glue, Azure Data Factory, Databricks, BigQuery, Dataflow, Dataproc) Would you like to join us as we work hard, have fun and make history? Apply for this job indicates More ❯

role: 5+ years of experience in Data Engineering: SQL, DWH (Redshift or Snowflake), Python (PySpark), Spark and associated data engineering jobs. Experience with AWS ETL pipeline services: Lambda, S3, EMR/Glue, Redshift(or Snowflake), step-functions (Preferred) Experience with building and supporting cloud based ETL (Extract Transform Load) Data Pipelines Good to have working experience on RESTful API More ❯

complex business requirements and drive decision-making. Your skills and experience Proficiency with AWS Tools: Demonstrable experience using AWS Glue, AWS Lambda, Amazon Kinesis, Amazon EMR , Amazon Athena, Amazon DynamoDB, Amazon Cloudwatch, Amazon SNS and AWS Step Functions. Programming Skills: Strong experience with modern programming languages such More ❯

schema), and data integration patterns. Hands-on experience with SQL and relational databases (e.g., Oracle, SQL Server, PostgreSQL). Familiarity with AWS data services such as S3, Redshift, Glue, EMR, Lambda, or RDS . Knowledge of scripting languages (e.g., Python, Shell) for automation and orchestration. Experience working in Agile environments and using tools such as JIRA , Git , or CI More ❯

schema), and data integration patterns. Hands-on experience with SQL and relational databases (e.g., Oracle, SQL Server, PostgreSQL). Familiarity with AWS data services such as S3, Redshift, Glue, EMR, Lambda, or RDS . Knowledge of scripting languages (e.g., Python, Shell) for automation and orchestration. Experience working in Agile environments and using tools such as JIRA , Git , or CI More ❯

Hadoop HDFS, and Apache Druid. Basic understanding of Data Lakehouse architectures, data modeling techniques, ETL processes, and relational databases (e.g., MySQL). Experience with AWS services, such as Glue, EMR and Lambda. Experience with workflow orchestration tools, such as Apache Airflow and Azkaban. Knowledge of NoSQL databases, including HBase. Strong problem-solving skills with a keen attention to detail. More ❯

Hadoop HDFS, and Apache Druid. Basic understanding of Data Lakehouse architectures, data modeling techniques, ETL processes, and relational databases (e.g., MySQL). Experience with AWS services, such as Glue, EMR and Lambda. Experience with workflow orchestration tools, such as Apache Airflow and Azkaban. Knowledge of NoSQL databases, including HBase. Strong problem-solving skills with a keen attention to detail. More ❯

Hadoop HDFS, and Apache Druid. Basic understanding of Data Lakehouse architectures, data modeling techniques, ETL processes, and relational databases (e.g., MySQL). Experience with AWS services, such as Glue, EMR and Lambda. Experience with workflow orchestration tools, such as Apache Airflow and Azkaban. Knowledge of NoSQL databases, including HBase. Strong problem-solving skills with a keen attention to detail. More ❯

Hadoop HDFS, and Apache Druid. Basic understanding of Data Lakehouse architectures, data modeling techniques, ETL processes, and relational databases (e.g., MySQL). Experience with AWS services, such as Glue, EMR and Lambda. Experience with workflow orchestration tools, such as Apache Airflow and Azkaban. Knowledge of NoSQL databases, including HBase. Strong problem-solving skills with a keen attention to detail. More ❯

be working on complex data problems in a challenging and fun environment, using some of the latest Big Data open-source technologies like Apache Spark, as well as Amazon Web Service technologies including Elastic MapReduce, Athena and Lambda to develop scalable data solutions. Key Responsibilities: Adhering to Company Policies and Procedures with respect to Security, Quality and Health More ❯

in building data and science solutions to drive strategic direction? Based in Tokyo, the Science and Data Technologies team designs, builds, operates, and scales the data infrastructure powering Amazon's retail business in Japan. Working with a diverse, global team serving customers and partners worldwide, you can make a significant impact while continuously learning and experimenting with cutting … software engineers and business teams to identify and implement strategic data opportunities. Key job responsibilities Your key responsibilities include: - Create data solutions with AWS services such as Redshift, S3, EMR, Lambda, SageMaker, CloudWatch etc. - Implement robust data solutions and scalable data architectures. - Develop and improve the operational excellence, data quality, monitoring and data governance. BASIC QUALIFICATIONS - Bachelor's degree … 3+ years of experience with data modeling, data warehousing, ETL/ELT pipelines and BI tools. - Experience with cloud-based big data technology stacks (e.g., Hadoop, Spark, Redshift, S3, EMR, SageMaker, DynamoDB etc.) - Knowledge of data management and data storage principles. - Expert-level proficiency in writing and optimizing SQL. - Ability to write code in Python for data processing. - Business More ❯

Amazon strives to be the world's most customer-centric company, where customers can research and purchase anything they might want online. We set big goals and are looking for people who can help us reach and exceed them. The CPT Data Engineering & Analytics (DEA) team builds and maintains critical data infrastructure that enhances seller experience and protects … the privacy of Amazon business partners throughout their lifecycle. We are looking for a strong Data Engineer to join our team. The Data Engineer I will work with well-defined requirements to develop and maintain data pipelines that help internal teams gather required insights for business decisions timely and accurately. You will collaborate with a team of Data … of distributed systems concepts from data storage and compute perspective - Ability to work effectively in a team environment PREFERRED QUALIFICATIONS - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions - Familiarity with big data technologies (Hadoop, Spark, etc.) - Knowledge of data security and privacy best practices - Strong problem-solving and analytical More ❯

Amazon Retail Financial Intelligence Systems is seeking a seasoned and talented Senior Data Engineer to join the Fortune Platform team. Fortune is a fast growing team with a mandate to build tools to automate profit-and-loss forecasting and planning for the Physical Consumer business. We are building the next generation Business Intelligence solutions using big data technologies … such as Apache Spark, Hive/Hadoop, and distributed query engines. As a Data Engineer in Amazon, you will be working in a large, extremely complex and dynamic data environment. You should be passionate about working with big data and are able to learn new technologies rapidly and evaluate them critically. You should have excellent communication skills and … 3+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines - Experience with SQL PREFERRED QUALIFICATIONS - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions - Experience with non-relational databases/data stores (object storage, document or key-value stores, graph databases, column-family databases) Our More ❯

to be successful in this role: Experience developing, testing, and deploying data pipelines, data lakes, data warehouses, and data marts using ideally AWS services such as S3, Glue, Athena, EMR, Kinesis, and Lambda Understanding of the principles behind designing and implementing data lake, lake house and/or data mesh architecture Problem solving skill with basic knowledge of the … with team members, stakeholders and end users conveying technical concepts in a comprehensible manner Skills across the following data competencies: SQL (AWS Athena/Hive/Snowflake) Hadoop/EMR/Spark/Scala Data structures (tables, views, stored procedures) Data Modelling - star/snowflake Schemas, efficient storage, normalisation Data Transformation DevOps - data pipelines Controls - selection and build Reference More ❯

in SQL. Familiarity with one scripting language, preferably Python. Experience with Apache Airflow & Apache Spark. Solid understanding of cloud data services: AWS services such as S3, Athena, EC2, RedShift, EMR (Elastic MapReduce), EKS, RDS (Relational Database Services) and Lambda. Nice to have: Understanding of ML Models. Understanding of containerisation and orchestration technologies like Docker/Kubernetes. Relevant knowledge or More ❯

in SQL. Familiarity with one scripting language, preferably Python. Experience with Apache Airflow & Apache Spark. Solid understanding of cloud data services: AWS services such as S3, Athena, EC2, RedShift, EMR (Elastic MapReduce), EKS, RDS (Relational Database Services) and Lambda. Nice to have Understanding of ML Models. Understanding of containerisation and orchestration technologies like Docker/Kubernetes. Relevant knowledge or More ❯