19 of 19 Amazon EMR Jobs in the UK

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 ...

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 ...

optimise scalable data models that support analytics and machine learning workloads. Solid working knowledge of AWS data services (e.g., S3, Kinesis, Glue, Redshift, Lambda, EMR) or Azure equivalents (e.g., ADF, Synapse, Fabric, Azure Functions). Familiarity with Palantir Foundry or Gotham is a significant advantage. Experience working within Data ...

optimise scalable data models that support analytics and machine learning workloads. Solid working knowledge of AWS data services (e.g., S3, Kinesis, Glue, Redshift, Lambda, EMR) or Azure equivalents (e.g., ADF, Synapse, Fabric, Azure Functions). Familiarity with Palantir Foundry or Gotham is a significant advantage. Experience working within Data ...

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. ...

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. ...

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 ...

frameworks. Key Responsibilities Design and develop scalable, testable data pipelines utilizing Python and Apache Spark. Orchestrate data workflows using AWS services including Glue, EMR Serverless, Lambda, and S3. Apply industry-standard software engineering practices such as version control, CI/CD, modular design, and automated testing. Contribute ...

have: experience with ThoughtSpot, automotive or adjacent domains Tech Stack (experience We Value) Heavily AWS‐based (e.g., S3, Lake Formation, Glue, Athena/Redshift, EMR, Kinesis); transformation and modelling (SQL, dbt, Spark); orchestration (Airflow/Dagster/Prefect); languages (Python/SQL); CI/CD & IaC (GitHub/GitLab ...

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 ...

/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. ...

pipelines and infrastructure that power our analytics, machine learning, and business intelligence initiatives. You'll work with cutting-edge technologies like Python, PySpark, AWS EMR, and Snowflake, and collaborate across teams to ensure data is clean, reliable, and actionable. Responsibilities: - Build and maintain scalable ETL pipelines using Python … PySpark to support data ingestion, transformation, and integration - Develop and optimize distributed data workflows on AWS EMR for high-performance processing of large datasets - Design, implement, and tune Snowflake data warehouses to support analytical workloads and reporting needs - Partner with data scientists, analysts, and product teams to deliver reliable ...

About Reward Founded in 2001, Reward is an industry leader transforming the world of customer engagement and commerce media. Operating in 15 countries across Europe, Middle East and Asia, Reward's cloud-based API platform ...

About Reward Founded in 2001, Reward is an industry leader transforming the world of customer engagement and commerce media. Operating in 15 countries across Europe, Middle East and Asia, Reward’s cloud-based API platform ...

About Reward Founded in 2001, Reward is an industry leader transforming the world of customer engagement and commerce media. Operating in 15 countries across Europe, Middle East and Asia, Reward’s cloud-based API platform ...

Bring Proven experience in DevOps or a similar engineering role. Proven experience deploying and managing AWS infrastructure (EC2, S3, RDS, Lambda, Glue, EMR, VPC, IAM, Redshift, etc.). Strong background in Terraform for infrastructure as code. Expertise in CI/CD automation using GitHub Actions. Hands-on experience managing ...

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 ...