1 to 25 of 35 Amazon Redshift Jobs in Berkshire

Java Developer – Financial Technology – London/Hybrid (INSIDE IR35) (Key skills: Java, Spring Boot, Kubernetes, AWS EKS, Amazon Redshift, PostgreSQL, RESTful APIs, CI/CD, Microservices, iOS/Android Native, Agile, Financial Services) Are you a highly skilled Java Developer with a passion for building scalable, high-performance financial systems? Do you enjoy working with cutting-edge technologies … integrated with modern mobile and analytics platforms. As part of a collaborative, Agile development team, you will be responsible for building robust microservices, managing data pipelines across PostgreSQL and Amazon Redshift , and delivering performant, secure RESTful APIs used across web and mobile platforms. You’ll work closely with iOS and Android engineers to ensure seamless end-to-end More ❯

experience across data engineering, cloud computing, or data warehousing Minimum 2 years in hands-on development capacity Expertise in one or more modern cloud data platforms: Snowflake, Databricks, AWS Redshift, Microsoft Fabric, or similar Understanding of data modelling principles, dimensional modelling, and database design Proficiency in SQL and query optimization Comprehensive knowledge of ETL/ELT processes and data More ❯

innovation and technical excellence. Your Profile Essential skills/knowledge/experience: Deep hands-on experience with AWS Cloud-native data platforms, including: AWS Glue, Lambda, Step Functions, Athena, Redshift, S3, CloudWatch AWS SDKs, Boto3, and serverless architecture patterns Strong programming skills in Python and Apache Spark Proven experience in Snowflake data engineering, including: Snowflake SQL, Snowpipe, Streams & Tasks More ❯

and data pipeline design. Hands-on experience with data lakehouse, warehouse, and streaming data architectures. Working knowledge of SQL, Python, and relevant data engineering frameworks (e.g. Databricks, Synapse, Snowflake, Redshift). Experience designing data platforms leveraging PaaS and SaaS solutions. Solid understanding of information governance, metadata management, and master data management principles. Experience leading data design across full project More ❯

data engineering experience , including at least 2 years hands-on with modern data platforms. Strong proficiency in SQL , data modelling, and query optimisation. Practical experience with Snowflake, Databricks, AWS Redshift, or Microsoft Fabric . Solid understanding of ETL/ELT pipelines and data warehousing principles . Strong communication and problem-solving skills. Ability to work both independently and collaboratively More ❯

and big data platforms. Knowledge of data modeling, replication, and query optimization. Hands-on experience with SQL and NoSQL databases is desirable. Familiarity with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) would be beneficial. Data Platform Management: Comfortable operating in hybrid environments (cloud and on-prem). Experience integrating diverse data sources and systems. Understanding of secure data transfer More ❯

and big data platforms. Knowledge of data modeling, replication, and query optimization. Hands-on experience with SQL and NoSQL databases is desirable. Familiarity with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) would be beneficial. Data Platform Management: Comfortable operating in hybrid environments (cloud and on-prem). Experience integrating diverse data sources and systems. Understanding of secure data transfer More ❯

AWS (preferred) or Azure , and experience managing data pipelines in the cloud. Strong skills in Python and SQL , with a solid grasp of data warehousing concepts. Experience with DBT , Redshift , or Postgres , and familiarity with BI tools (Power BI preferred). Proven understanding of CI/CD principles , DevOps, and infrastructure automation. Excellent communication skills — able to collaborate across More ❯

years of experience in data engineering or analytics, including designing and delivering enterprise grade data solutions Strong hands-on experience with Snowflake (or comparable cloud data warehouses like BigQuery, RedShift, Synapse) including data modelling, performance tuning and cost management Familiarity with SQL best practices, ELT patterns, and modern data transformation frameworks such as dbt Competence in at least one More ❯

sports betting, gaming, or a similar high-volume data environment. Strong coding skills in Python and advanced SQL expertise. Hands-on experience with AWS data tools (S3, Glue, Lambda, Redshift, Kinesis, etc.). Proficiency with Power BI (or equivalent data visualisation tools). Solid experience building and supporting data models for forecasting, pricing, or predictive analytics. Strong communication and More ❯

Snowflake development and optimisation. Strong skills in Python and SQL for ELT/ETL and transformation workflows. Experience with cloud native storage and compute tools: S3, Data Lake, ADF, Redshift, Synapse, etc. Familiarity with CI/CD pipelines, test automation, and DevOps practices in data workflows. Stakeholder management Career & Development Opportunities Structured career progression with increasing exposure to technical More ❯

branching, merging, pull requests). Preferred Qualifications (A Plus) Experience with a distributed computing framework like Apache Spark (using PySpark). Familiarity with cloud data services ( AWS S3/Redshift, Azure Data Lake/Synapse, or Google BigQuery/Cloud Storage ). Exposure to workflow orchestration tools ( Apache Airflow, Prefect, or Dagster ). Bachelor's degree in Computer Science More ❯

Engineer, particularly in data modelling. Strong SQL and hands-on dbt experience. Ability to convert business requirements into logical, scalable data models. Knowledge of cloud data platforms (e.g., Snowflake, Redshift, BigQuery). Strong communication and documentation skills. Structured, detail-oriented mindset. Desirable: Experience with semantic modelling tools (e.g., dbt SL, LookML). Familiarity with workflow orchestration and BI tooling. More ❯

branching, merging, pull requests). Preferred Qualifications (A Plus) Experience with a distributed computing framework like Apache Spark (using PySpark). Familiarity with cloud data services ( AWS S3/Redshift, Azure Data Lake/Synapse, or Google BigQuery/Cloud Storage ). Exposure to workflow orchestration tools ( Apache Airflow, Prefect, or Dagster ). Bachelor's degree in Computer Science More ❯

. Hands-on experience with data orchestration tools (Airflow, dbt, Dagster, or Prefect). Solid understanding of cloud data platforms (AWS, GCP, or Azure) and data warehousing (Snowflake, BigQuery, Redshift). Experience with streaming technologies (Kafka, Kinesis, or similar). Strong knowledge of data modelling, governance, and architecture best practices . Excellent leadership, communication, and stakeholder management skills. NICE More ❯

optimize data pipelines and workflows using modern tools (e.g., dbt, Airflow, SQL, Python). Take ownership of large-scale analytics platforms and data warehouse solutions (such as Snowflake, BigQuery, Redshift). Mentor and guide engineers across analytics and data engineering disciplines. Ensure solutions adhere to best practices for data governance, integrity, and scalability. Drive continuous innovation in data orchestration More ❯

business impact. Skills Excellent communication skills (written, verbal, and presentation). Strong organisational and planning abilities. Advanced technical expertise across Tableau, MySQL, Python, and modern BI tools (e.g. AWS Redshift). Ability to translate complex data into clear, actionable insights for business leaders. Knowledge Advanced knowledge of statistics and data modelling. Data visualisation and storytelling best practice. Data pipelines More ❯

libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/or implementing data pipelines from major financial market data vendors (Bloomberg, Refinitiv, Factset....) SDLC and DevOps: Git, Docker, Jenkins/TeamCity More ❯

path to production Worked with AWS as a cloud platform Extensive hands-on experience with modern data technologies, ETL tools (e.g. Kafka, Flink, DBT etc.), data storage (e.g. Snowflake, Redshift, etc.) and also IaC (e.g. Terraform, CloudFormation) Software development experience with one or more languages (e.g. Python, Java, Scala, Go) Pragmatic approach to solving problems Nice to have: keen More ❯

monitoring and observer ability toolsets inc. Splunk, Datadog Experience using Github Actions Experience using AWS RDS/SQL based solutions Experience using containerization in AWS Working data warehouse knowledge Redshift and Snowflake preferred Working with IaC – Terraform and Cloud Formation Working understanding of scripting languages including Python and Shell Experience working with streaming technologies inc. Kafka, Apache Flink Experience More ❯

your team. Lead by example — fostering collaboration, accountability, and agile delivery in every sprint. 🧠 What You Bring Expertise in AWS : Hands-on experience with Python, Glue, S3, Airflow, DBT, Redshift, and RDS. Proven success in end-to-end data engineering — from ingestion to insight. Strong leadership and communication skills, with a collaborative, solution-driven mindset. Experience working in Agile More ❯

across BI, Data Engineering, and AI teams SKILLS AND EXPERIENCE Required: 5+ years’ experience in BI Operations or Production Support (AWS environment) Strong SQL and AWS BI stack expertise (Redshift, Glue, Airflow, S3, Step Functions) Proficiency with Power BI or similar reporting tools Experience with incident, change, and problem management (ITIL framework) Proven ability to optimise workflows and automate More ❯

Java) and SQL Deep experience with data pipeline orchestration tools (Airflow, dbt, Dagster, Prefect) Strong knowledge of cloud data platforms (AWS, GCP, or Azure) and data warehousing (Snowflake, BigQuery, Redshift) Hands-on experience with streaming technologies (Kafka, Kinesis, or similar) Solid understanding of data modelling, governance, and architecture best practices Familiarity with machine learning pipelines or AI model integration More ❯

techniques. What You’ll 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 Linux environments and scripting (Python, Bash More ❯

technology strategy for a high-growth Financial Services or FinTech firm. A Data Engineering background (or similar) with excellent hands-on experience and understanding of Data Warehouse (e.g. BigQuery, Redshift, Snowflake, Databricks), orchestration, data modelling and cloud technology (AWS, GCP, Azure) Strong AI literacy, including leveraging AI to pull insights from structured and unstructured data Excellent communication skills with More ❯