1 to 25 of 107 Amazon Redshift Jobs in the Thames Valley

from various sources into AWS data stores for both batch and streaming data ingestion. AWS Expertise: Utilize your expertise in AWS services such as Amazon EMR, S3, AWS Glue, Amazon Redshift, AWS Lambda, and more to build and optimize data solutions. Data Modeling: Design and implement data … a related field. 5 to 8 years of experience in data engineering, including working with AWS services. Proficiency in AWS services like S3, Glue, Redshift, Lambda, and EMR. Knowledge of Cloudera-based Hadoop is a plus. Strong ETL development skills and experience with data integration tools. Knowledge of data More ❯

role. Proven experience designing and delivering enterprise data strategies . Exceptional communication and stakeholder management skills. Expertise in enterprise-grade data warehouses (Snowflake, BigQuery, Redshift). Hands-on experience with Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of More ❯

broad exposure, technical ownership, and the opportunity to influence firm-wide data architecture. Key Responsibilities Build scalable data pipelines using AWS (Glue, Lambda, EventBridge, Redshift) Ingest, normalise, and validate data from vendors (Bloomberg, Refinitiv, exchanges) Enhance platform capabilities for historical, real-time, and alternative datasets Monitor data quality and More ❯

while fostering a positive and inclusive team culture What we’re looking for: Hands-on experience building and maintaining cloud-based data systems (e.g., Redshift, BigQuery, Snowflake) Strong coding skills in languages commonly used for data work (e.g., Python, Java, Scala) Deep understanding of ETL/ELT tools and More ❯

Strong stakeholder experience with an ability to work with both technical and non-technical stakeholders.//Proven experience with AWS services (e.g. S3, Redshift, Lambda, ECS, Eventbridge, CloudWatch, Athena etc.).//Proficient in Python & SQL.//Experience with Terraform to manage IaC.//Strong More ❯

/principal level. Strong stakeholder management skills, capable of working with both technical and non-technical stakeholders. Proven experience with AWS services (e.g., S3, Redshift, Lambda, ECS, Eventbridge, CloudWatch, Athena). Proficiency in Python & SQL. Experience with Terraform for Infrastructure as Code (IaC). Deep understanding of data engineering More ❯

optimization, and stored procedures. Strong coding skills in Python for data transformation, scripting, and automation. Experience with cloud platforms such as AWS (e.g., S3, Redshift, Lambda) , Azure (e.g., Data Factory, Synapse) , or GCP (e.g., BigQuery, Cloud Functions) . Familiarity with data orchestration tools (e.g., Airflow, dbt) and version control More ❯

to detail with strong analytical and problem-solving skills. Excellent communication and stakeholder engagement skills. Experience with cloud data platforms (e.g., Azure Synapse, AWS Redshift, Google BigQuery). Knowledge of data governance frameworks and data quality management. Competence in data modelling and database design techniques. Experience working in agile More ❯

to detail with strong analytical and problem-solving skills. Excellent communication and stakeholder engagement skills. Experience with cloud data platforms (e.g., Azure Synapse, AWS Redshift, Google BigQuery). Knowledge of data governance frameworks and data quality management. Competence in data modelling and database design techniques. Experience working in agile More ❯

to detail with strong analytical and problem-solving skills. Excellent communication and stakeholder engagement skills. Experience with cloud data platforms (e.g., Azure Synapse, AWS Redshift, Google BigQuery). Knowledge of data governance frameworks and data quality management. Competence in data modelling and database design techniques. Experience working in agile More ❯

to detail with strong analytical and problem-solving skills. Excellent communication and stakeholder engagement skills. Experience with cloud data platforms (e.g., Azure Synapse, AWS Redshift, Google BigQuery). Knowledge of data governance frameworks and data quality management. Competence in data modelling and database design techniques. Experience working in agile More ❯

to detail with strong analytical and problem-solving skills. Excellent communication and stakeholder engagement skills. Experience with cloud data platforms (e.g., Azure Synapse, AWS Redshift, Google BigQuery). Knowledge of data governance frameworks and data quality management. Competence in data modelling and database design techniques. Experience working in agile More ❯

code into production services (CI/CD, containers etc) Strong SQL and data-management skills; experience querying large analytical databases (Snowflake highly desirable, but Redshift/BigQuery/ClickHouse etc. also welcome). PREFERRED QUALIFICATIONS: Meteorological understanding/experience with weather modelling Prior knowledge or experience in the power More ❯

large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data Access & Engineering Collaboration : Comfort working with cloud data warehouses (e.g., Snowflake, Databricks, Redshift, BigQuery) Familiarity with data pipelines and orchestration tools like Airflow Work closely with Data Engineers to ensure model-ready data and scalable pipelines. Nice More ❯

platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯

platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯

platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯

platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯

platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯

scalable AWS data solutions while mentoring junior engineers. Key Responsibilities: Lead the development and implementation of AWS data components, including Firehose, Glue, Lambda, Athena, Redshift, and Quicksight. Support junior engineers through technical guidance, mentoring, and task leadership. Collaborate with cloud architects to evolve our MVP data platform toward a More ❯

AWS. Collaborate with engineering teams to ensure a smooth transition and system stability. Languages & Scripting: Python (primary scripting language for Lambda functions) SQL (BigQuery, Redshift) R (not essential but beneficial for interpreting existing scripts) Cloud & Infrastructure: AWS services including Lambda, API Gateway, S3, CloudWatch, Kinesis Firehose Terraform for infrastructure More ❯

a strong focus on Data work. • Strong proficiency in leading big data technologies (e.g., Hadoop, Spark, Hive). • Familiarity with data warehousing solutions (e.g., Redshift, BigQuery, Snowflake). • Strong problem-solving skills and attention to detail. • Excellent communication and collaboration skills. Bonus • Experience working across the complete data stack. More ❯

warehousing, data lake/lakehouse architectures, and cloud-native analytics platforms. Hands-on experience with SQL and cloud data platforms (e.g., Snowflake, Azure, AWS Redshift, GCP BigQuery). Experience with BI/analytics tools (e.g., Power BI, Tableau) and data visualization best practices. Strong knowledge of data governance, data More ❯

data transformation and modeling in a modern data stack. Proficiency in SQL , Python , and PySpark . Experience with AWS services such as S3, Athena, Redshift, Lambda, and CloudWatch. Familiarity with data warehousing concepts and modern data stack architectures. Experience with CI/CD pipelines and version control (e.g., Git More ❯

Implement best practices for cloud security, cost optimization, monitoring, and alerting. - Support the deployment and maintenance of modern data stacks (e.g., Snowflake, Databricks, BigQuery, Redshift). - Design and enforce networking, identity access, and compliance standards aligned with client requirements. - Write documentation, runbooks, and client-facing reports to support infrastructure More ❯