1 to 25 of 37 Amazon EMR Jobs in the UK

Have: ● Familiarity with data security, privacy, and compliance frameworks ● Exposure to machine learning pipelines, MLOps, or AI-driven data products ● Experience with big data platforms and technologies such as EMR, Databricks, Kafka, Spark ● Exposure to AI/ML concepts and collaboration with data science or AI teams. ● Experience integrating data solutions with AI/ML platforms or supporting AI More ❯

Have: ● Familiarity with data security, privacy, and compliance frameworks ● Exposure to machine learning pipelines, MLOps, or AI-driven data products ● Experience with big data platforms and technologies such as EMR, Databricks, Kafka, Spark ● Exposure to AI/ML concepts and collaboration with data science or AI teams. ● Experience integrating data solutions with AI/ML platforms or supporting AI More ❯

in AWS cloud technologies for ETL 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. You’ll be using your technical skills More ❯

in AWS cloud technologies for ETL 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. You’ll be using your technical skills More ❯

in AWS cloud technologies for ETL 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. You’ll be using your technical skills More ❯

the following: Python, SQL, Java 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, CI/CD, and code More ❯

in AWS cloud technologies for ETL 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 . Essential requirements You thrive in problem-solving and analytical thinking You enjoy collaborating with multiple stakeholders in a fast-paced environment Experience in More ❯

Experience: Proven experience as a Senior Data Engineer in a large-scale or complex environment. Strong hands-on expertise with AWS data services (e.g., S3, Glue, Lambda, Redshift, Athena, EMR). Experience building data lakes and modern data platforms from the ground up. Proficiency with Python, SQL, and orchestration tools such as Airflow or dbt. Strong understanding of data More ❯

Main Skills Needed: Proven experience in BI and data platform testing, including ETL, data warehouse, and reporting validation. Strong hands-on knowledge of AWS data tools (Glue, Redshift, Athena, EMR, Lambda). Confident with Power BI, SQL, Python/PySpark, and QA automation tools. Solid grasp of data governance, GDPR, and data quality standards. Background in Agile delivery and More ❯

Main Skills Needed: Proven experience in BI and data platform testing, including ETL, data warehouse, and reporting validation. Strong hands-on knowledge of AWS data tools (Glue, Redshift, Athena, EMR, Lambda). Confident with Power BI, SQL, Python/PySpark, and QA automation tools. Solid grasp of data governance, GDPR, and data quality standards. Background in Agile delivery and More ❯

Main Skills Needed: Proven experience in BI and data platform testing, including ETL, data warehouse, and reporting validation. Strong hands-on knowledge of AWS data tools (Glue, Redshift, Athena, EMR, Lambda). Confident with Power BI, SQL, Python/PySpark, and QA automation tools. Solid grasp of data governance, GDPR, and data quality standards. Background in Agile delivery and More ❯

Main Skills Needed: Proven experience in BI and data platform testing, including ETL, data warehouse, and reporting validation. Strong hands-on knowledge of AWS data tools (Glue, Redshift, Athena, EMR, Lambda). Confident with Power BI, SQL, Python/PySpark, and QA automation tools. Solid grasp of data governance, GDPR, and data quality standards. Background in Agile delivery and More ❯

with recovery, optimisation, and automation. Troubleshoot issues and contribute to process/documentation improvements. Experience: Essential: Strong AWS services experience (S3, Redshift, Athena, Glue, Batch, Lambda, Step Functions, SQS, EMR). Terraform (IaC), Airflow (orchestration), CI/CD (YAML, GitLab/GitHub). Python, SQL, Bash. AWS security/IAM, VPC networking, Docker. Backup and disaster recovery knowledge. Problem More ❯

AWS, DBT and Snowflake. Self starter with a proven track record of delivering work to high standard with minimal guidance. Desirable Experience of ETL technologies AWS exposure (Athena, Glue, EMR, Step functions) Experience of relational database technologies (MS SQL Server, Redshift, Aurora) Experience with data solution BAU processes (ETL, table refresh, amongst others) We work with Textio to make More ❯

as Airflow, DBT, Databricks, and data catalogue/observability tools (e.g. Monte Carlo, Atlan, Datahub). Knowledge of cloud infrastructure (AWS or GCP) - including services such as S3, RDS, EMR, ECS, IAM. Experience with DevOps tooling, particularly Terraform and CI/CD pipelines (e.g. Jenkins). A proactive, growth-oriented mindset with a passion for modern data and platform More ❯

migration, metadata, and master data management. Experienced delivering data analytics solutions and supporting AI initiatives. Hands on experience with cloud data platforms, ideally AWS (S3, Kinesis, Glue, Redshift, Lambda, EMR) and/or Azure (ADF, Synapse, Fabric, AzureFunctions). Familiarity with modern data lakehouse environments such as Databricks, Snowflake, or Microsoft Fabric (highly desirable). Experience with Palantir Foundry More ❯

data pipelines and architectures on the Amazon Web Services (AWS) cloud platform. Skilled in scalable, reliable, and efficient data solutions, often using AWS services like S3, Redshift, EMR, Glue, and Kinesis. This involves designing ETL processes, ensuring data security, and collaborating with other teams for data analysis and business requirements Role Overview: Job Title: Data AWS Engineer … up-to-date with the latest AWS services and technologies to improve data engineering solutions. Key Skills: AWS Services: Strong understanding and experience with AWS services like S3 , Redshift, EMR, Glue , Kinesis, and Lambda. Programming Languages: Proficiency in programming languages like Python or Java, used for designing and building data pipelines. SQL: Knowledge of SQL for querying and manipulating More ❯

similar role. Experience of deploying & managing cloud infrastructure for Data Solutions Hands-on experience of working with AWS services, including but not limited to EC2, S3, RDS, Lambda, Glue, EMR, VPC, IAM, Redshift, etc. Good experience in setting up reliable cloud networking that is highly secured. Experience of setting up standard cloud governance policies through IAM roles. Extensive experience More ❯

and/or algorithms, understanding of NLP algorithms Our technology stack Python and associated ML/DS libraries (scikit-learn, NumPy, LightGBM, Pandas, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc. MLOp/DevOps: Terraform, Docker, Airflow, MLFlow, NewRelic The interview process Recruiter Call (30 minutes) Meeting a Machine Learning Manager(30 minutes) Technical Interview with More ❯

Track record of delivering data analytics and AI/ML-enabling solutions across complex environments. Hands-on experience with cloud data platforms , ideally AWS (S3, Kinesis, Glue, Redshift, Lambda, EMR). Experience with Azure technologies (ADF, Synapse, Fabric, Azure Functions) is also valued. Strong understanding of modern data lakehouse architectures , such as Databricks , Snowflake , or Microsoft Fabric (highly desirable More ❯

move fast, stay compliant and take end-to-end responsibility for their products. Major elements of our platform include AWS (we make significant use of S3, RDS, Kinesis, EC2, EMR, ElastiCache, ElasticSearch and EKS). Elements of the platform will start to expand into GCP (Compute Engine, Cloud Storage, Google Kubernetes Engine and BigQuery). Other significant tools of More ❯

data management. Experience in developing data analytics and AI-driven solutions. Skilled in designing and automating data quality metrics and KPIs. Proficient with AWS (S3, Kinesis, Glue, Redshift, Lambda, EMR) and/or Azure (ADF, Synapse, Fabric, Functions). To be Considered.... Please either apply by clicking online or emailing me directly to henry.clay-davies@searchability.com For further information More ❯

data management. Experience in developing data analytics and AI-driven solutions. Skilled in designing and automating data quality metrics and KPIs. Proficient with AWS (S3, Kinesis, Glue, Redshift, Lambda, EMR) and/or Azure (ADF, Synapse, Fabric, Functions). To be Considered.... Please either apply by clicking online or emailing me directly to henry.clay-davies@searchability.com For further information More ❯

ML techniques, A/B testing methodologies, and experiment design. Solid background in ranking, recommendation, and retrieval systems. Familiarity with large-scale data tools (Hadoop, BigQuery, Amazon EMR, etc.). Experience with BI tools and visualization platforms such as Tableau, Qlik, or MicroStrategy. Bonus: Experience with geospatial data and advanced analytics platforms. More ❯

ML techniques, A/B testing methodologies, and experiment design. Solid background in ranking, recommendation, and retrieval systems. Familiarity with large-scale data tools (Hadoop, BigQuery, Amazon EMR, etc.). Experience with BI tools and visualization platforms such as Tableau, Qlik, or MicroStrategy. Bonus: Experience with geospatial data and advanced analytics platforms. More ❯