13 of 13 Amazon EMR Jobs in the North of England

source-code management. Strong troubleshooting and problem-solving skills. AWS Experience Candidates should have practical experience with relevant AWS data services, such as: Amazon S3 AWS Glue Amazon Redshift AWS Lambda Amazon Athena Amazon RDS AWS IAM Amazon CloudWatch Experience with services such as Kinesis, EMR, Step Functions or MWAA/Airflow would be advantageous. AWS data engineering roles commonly use services such as S3, Glue, Redshift, Lambda, Kinesis ...

data processing workflows. Root cause analysis Perform data analysis to identify and resolve root causes of pipeline failures and data quality issues - including reviewing EMR output logs and CloudWatch metrics. Apply understanding of dimensional data models and slowly changing dimensions (SCD) to design and maintain well-structured, analytically trusted … development and data processing SQL - used for querying, transformation, and validation across data stores PySpark - for distributed data processing using Apache Spark on AWS EMR Familiarity with basic data structures for constructing robust, scalable solutions Data processing & orchestration Apache Spark - understanding of distributed data processing architecture and execution Apache ...

Server to AWS, including target modelling, cutover approach, reconciliation strategy and technical risk management. Design and build the real‐time data architecture using Amazon MSK/Apache Kafka and PySpark Structured Streaming (evaluating Apache Flink where it is the better fit), including event schema governance, exactly‐once semantics … Essentials: Deep, hands‐on expertise across core AWS data services such as AWS Glue, AWS Lambda, AWS S3, AWS Redshift, and Amazon EMR, with the ability to make and defend architectural decisions. Advanced proficiency in Python and SQL, including PySpark for large‐scale batch and streaming processing ...

Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse platforms on AWS (EMR, Databricks or Snowflake) - Experience building data platforms such as Data Lakes, Lakehouses or Data Meshes that underpin analytics and AI workloads - Understanding of Data ...

Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse platforms on AWS (EMR, Databricks or Snowflake) - Experience building data platforms such as Data Lakes, Lakehouses or Data Meshes that underpin analytics and AI workloads - Understanding of Data ...

Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse platforms on AWS (EMR, Databricks or Snowflake) - Experience building data platforms such as Data Lakes, Lakehouses or Data Meshes that underpin analytics and AI workloads - Understanding of Data ...

ingesting, transforming and processing data from multiple sources Design and implement data solutions using AWS services such as S3, Glue, Lambda, Athena, Redshift, EMR and related technologies Design data models and storage approaches appropriate to analytical and operational requirements Develop solutions using Python, SQL and modern data engineering frameworks … environments Strong experience designing and delivering data solutions on AWS Strong knowledge of AWS data services such as S3, Glue, Lambda, Athena, Redshift and EMR, with experience selecting the appropriate services for different requirements Strong Python and SQL skills Experience designing and building scalable ETL/ELT pipelines ...

Experience: Understanding of data processing using Apache Spark and Apache Airflow for task orchestration Use of Python, SQL, and familiarity with PySpark Understanding of EMR and reviewing output logs Use of Jupyter notebooks and/or Amazon Athena to query and validate data Data analysis to identify … changing dimensions/historic data capture Use of AWS console and services such as, but not limited to; CloudWatch, IAM, S3, Glue, ECR, EC2, EMR, Dynamo DB and LakeFormation Familiarity with Amazon Textract and Comprehend Understanding of both server-side and client-side encryption Use of GitLab ...

large-scale data platform or data warehouse migration (cutover, reconciliation, parallel running, decommissioning) Deep, hands-on AWS data experience: Glue, Lambda, S3, Redshift and EMR Advanced Python, PySpark and SQL Production experience with Kafka or Amazon MSK, including Spark Structured Streaming Hands-on experience with Apache Iceberg ...

What they're looking for: Previous experience as a Technical Lead (hands-on) Deep, hands-on AWS data experience: Glue, Lambda, S3, Redshift and EMR Advanced Python, PySpark and SQL Production experience with Kafka or Amazon MSK, including Spark Structured Streaming Hands-on experience with Apache Iceberg ...

Agile delivery mindset. On AWS, you’re fluent across the core services, for example: Storage & Lakehouse: RDS, DynamoDB, S3, SageMaker Lakehouse Processing & ETL: Glue, EMR, Athena, CDC/DMS, DataBrew, Kinesis, dbt Data management & metadata: Lake Formation, Glue Data Catalog, SageMaker Catalog/DataZone AI: Bedrock (including AgentCore … decision‐making. AI : You understand how AI is built and deployed in modern data platforms (Databricks, Snowflake) and cloud‐native services like Amazon Bedrock, with enough depth to guide teams and advise clients, spanning LLMs and SLMs, agentic automation, Human in the Loop and MLOps. Data Architecture Design ...

does Build and maintain the batch and ELT pipelines the ML work sits on, using Python, PySpark, and cloud data services (e.g., AWS Glue, EMR, S3, Redshift, Athena, or the Databricks/Snowflake equivalents), making sound decisions on architecture, data modelling, and tooling and weighing up trade-offs … need to be the person designing the model Have designed and operated production data pipelines on a modern cloud data platform, AWS (Glue, EMR, Redshift, S3/Lake Formation), Databricks, Snowflake or comparable, and can talk about which of those decisions would travel to a different one, and which ...

does Build and maintain the batch and ELT pipelines the ML work sits on, using Python, PySpark, and cloud data services (e.g., AWS Glue, EMR, S3, Redshift, Athena, or the Databricks/Snowflake equivalents), making sound decisions on architecture, data modelling, and tooling and weighing up trade-offs … need to be the person designing the model Have designed and operated production data pipelines on a modern cloud data platform, AWS (Glue, EMR, Redshift, S3/Lake Formation), Databricks, Snowflake or comparable, and can talk about which of those decisions would travel to a different one, and which ...