1 to 25 of 32 Amazon Redshift Jobs in the City of London

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 ❯

CD pipelines for data solutions Solid experience with cloud platforms (e.g., AWS, Azure, or GCP), and their data services. Deep understanding of data warehousing concepts and technologies (e.g., Snowflake, Redshift). Strong knowledge of ETL/ELT processes and tools. Solid experience of utilising PowerBI or similar visualisation tools Experience working with big data technologies and frameworks (e.g., Spark 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 ❯

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 ❯

and risk workflows. What you’ll bring Proven experience as a Data Engineer within financial services, ideally hedge funds or buy-side. Strong expertise in AWS (S3, Glue, Lambda, Redshift, Kinesis, etc.). Advanced skills in Python and SQL for building pipelines and optimising performance. Hands-on experience with Power BI for data visualisation and reporting. Strong understanding of More ❯

With Python (primary language) SQL Large-scale data workflows (ETL, transformation, analytics) Parquet and columnar data formats Cloud environments — experience with any major cloud provider is great AWS experience (Redshift, Lambda, ECS, S3) is nice to have , not required GCP/Azure backgrounds are equally welcome What You’ll Bring Solid professional experience developing in Python . Strong SQL 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 ❯

ERwin/ER/Studio/PowerDesigner) Cloud & big data expertise: batch + streaming ingestion, CI/CD (Azure DevOps, Terraform, AWS CodePipeline), cloud DBs (SQL Server, PostgreSQL, Oracle, Redshift, Synapse) Proficiency with Power BI , Tableau , or Qlik Advantageous: experience within Banking, Insurance, BFI, or Retail 💼 What’s On Offer Competitive salary + strong bonus scheme Private healthcare, critical 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 ❯

Familiarity with Airflow, Dagster or similar data orchestration frameworks Strong understanding of RESTful APIs as well as experience working with both synchronous and asynchronous endpoints Experience with Snowflake or Redshift with a strong understanding of SQL. Proficient in Python and Pandas Experience working with JSON and XML Strong understanding of cloud computing concepts and services (AWS preferably) Experience with 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 ❯

sources. Ensure the pipelines are optimized for performance, reliability, and maintainability. 🌳 AWS Expertise: Utilize AWS services for data storage, processing, and analytics. Leverage AWS technologies such as S3, Glue, Redshift, and others to build and maintain data solutions. Implement best practices for security and compliance in an AWS environment. 🌳 Python Programming: Demonstrate proficiency in Python programming for data processing 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 ❯

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 ❯

will: Architect, optimise, and deliver ELT pipelines and data workflows (using dbt, Airflow, SQL, Python). Own and evolve large-scale analytics platforms and data warehouse solutions (Snowflake, BigQuery, Redshift). Mentor engineers across analytics engineering and data engineering disciplines. Ensure data solutions meet best practices for governance, integrity, modelling, and scalability. Drive innovation in data orchestration, schema design 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 ❯

efficiency and deliver scalable, data-driven solutions. What you’ll bring: Strong ML Ops experience. Proficiency in Python and SQL . Hands-on cloud engineering experience with AWS & Azure (Redshift, Synapse). Familiarity with Terraform, Power BI, and Excel . A proactive, problem-solving mindset with strong collaboration skills. This role offers the chance to work within a progressive 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 ❯

will have the following skills and experience: Strong Python (python frameworks), backend development experience (3+ years) Experience working with AI/ML or big data systems. Familiarity with AWS , Redshift , or other cloud data platforms (GCP/Azure also welcome). Background in AdTech, MarTech or experience with Meta Marketing API or Google Ads API is a plus. Ability More ❯

Skills & Experience: 5+ years of experience building and maintaining data pipelines in production environments Strong Python and SQL skills (Pandas, PySpark, query optimisation) Cloud experience (AWS preferred) including S3, Redshift, Glue, Lambda Familiarity with data warehousing (Redshift, Snowflake, BigQuery) Experience with workflow orchestration tools (Airflow, Dagster, Prefect) Understanding of distributed systems, batch and streaming data (Kafka, Kinesis) Knowledge More ❯

Senior Data Engineer - AWS - London - £70,000 - £85,000 To be considered for this role, you must be SC cleared or eligible to obtain SC clearance. My client are seeking a Senior AWS Data Engineer to join an agile engineering More ❯

aligned to Data best practices. Liaison with IT Business Systems & Business Teams & Third Parties. Drive Continuous Improvement. Technical Skills Required: Azure Data Factory - 4 years’ experience AWS Data Services (Redshift, S3, Lambda) - Desirable. SSRS - hands-on experience. ETL - Design, Data Quality Frameworks & Pipeline Management. SQL - Star Schema - Data Modelling. Data Warehouse Design, Development & Testing. Data Warehousing Methodologies. User Support … Assurance/Store Discount/Well Being Programme/Cycle to Work Scheme/Electric Car Salary Sacrifice Scheme. Keywords: Data Engineer, Azure Data Factory, AWS, AWS Data Services, Redshift, S3, Lambda, Azure BI Technologies, ETL, Data Warehousing, Data Modelling & Kimball Methodology, Data Engineer, Power BI, SQL, ETL, SSRS, Data Engineer. Permanent, T6/MN/1292110-3. More ❯