76 to 100 of 166 Amazon Redshift Jobs

the team, promoting best practices and knowledge sharing. What Experience is Required Proven experience as a Data Engineer , ideally 4+ years in a similar role. Strong proficiency with SQL , Amazon Redshift , and preferably MySQL and QuickSight . Experience with AWS Glue , Python scripting , and building ETL/ELT data processes. Salary & Benefits £85,000 per annum plus excellent More ❯

implementing Power BI architectures at enterprise scale. Strong expertise in data modelling , ETL , and enterprise data architecture . Hands-on experience with AWS data services (e.g. Glue, S3, Lambda, Redshift). Experience building reusable data ingestion and transformation pipelines. Knowledge of metadata management , data governance , and data lineage practices. Skilled at integrating or enhancing existing BI solutions. Excellent stakeholder More ❯

Strong stakeholder management and communication skills, with the ability to translate technical outputs into business-friendly insights. Experience with Snowflake (or alternative cloud data warehouses such as BigQuery or Redshift). More ❯

Strong stakeholder management and communication skills, with the ability to translate technical outputs into business-friendly insights. Experience with Snowflake (or alternative cloud data warehouses such as BigQuery or Redshift). More ❯

Engineering projects Strong experience in Python/PySpark, Databricks & Apache Spark Hands on experience with both batch & streaming pipelines Strong experience in AWS and associated tooling (Eg, S3, Glue, Redshift, Lambda, Terraform etc) Experience designing Data Engineering platforms from scratch Alongside their commitment to work-life balance the business also has an extremely competitive benefits package including, but not More ❯

Engineering projects Strong experience in Python/PySpark, Databricks & Apache Spark Hands on experience with both batch & streaming pipelines Strong experience in AWS and associated tooling (Eg, S3, Glue, Redshift, Lambda, Terraform etc) Experience designing Data Engineering platforms from scratch Alongside their commitment to work-life balance the business also has an extremely competitive benefits package including, but not More ❯

innovation. Architect and optimise ELT pipelines and workflows using dbt, Airflow, SQL, and Python. Oversee the design and evolution of large-scale analytics platforms and data warehouses (Snowflake, BigQuery, Redshift). Ensure best practices in governance, modelling, data quality, and scalable system design. Drive continuous improvement in orchestration, schema design, transformation, and automation processes. Translate complex technical insights into More ❯

innovation. Architect and optimise ELT pipelines and workflows using dbt, Airflow, SQL, and Python. Oversee the design and evolution of large-scale analytics platforms and data warehouses (Snowflake, BigQuery, Redshift). Ensure best practices in governance, modelling, data quality, and scalable system design. Drive continuous improvement in orchestration, schema design, transformation, and automation processes. Translate complex technical insights into More ❯

innovation. Architect and optimise ELT pipelines and workflows using dbt, Airflow, SQL, and Python. Oversee the design and evolution of large-scale analytics platforms and data warehouses (Snowflake, BigQuery, Redshift). Ensure best practices in governance, modelling, data quality, and scalable system design. Drive continuous improvement in orchestration, schema design, transformation, and automation processes. Translate complex technical insights into More ❯

innovation. Architect and optimise ELT pipelines and workflows using dbt, Airflow, SQL, and Python. Oversee the design and evolution of large-scale analytics platforms and data warehouses (Snowflake, BigQuery, Redshift). Ensure best practices in governance, modelling, data quality, and scalable system design. Drive continuous improvement in orchestration, schema design, transformation, and automation processes. Translate complex technical insights into More ❯

innovation. Architect and optimise ELT pipelines and workflows using dbt, Airflow, SQL, and Python. Oversee the design and evolution of large-scale analytics platforms and data warehouses (Snowflake, BigQuery, Redshift). Ensure best practices in governance, modelling, data quality, and scalable system design. Drive continuous improvement in orchestration, schema design, transformation, and automation processes. Translate complex technical insights into More ❯

Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication), use Redshift for efficient loading strategies and write ETL pipelines that handle large volumes of data efficiently, with low latency. Location/WFH: You'll join a small but growing team More ❯

Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication), use Redshift for efficient loading strategies and write ETL pipelines that handle large volumes of data efficiently, with low latency. Location/WFH: You'll join a small but growing team More ❯

Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication), use Redshift for efficient loading strategies and write ETL pipelines that handle large volumes of data efficiently, with low latency. Location/WFH: You'll join a small but growing team More ❯

Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication), use Redshift for efficient loading strategies and write ETL pipelines that handle large volumes of data efficiently, with low latency. Location/WFH: You'll join a small but growing team More ❯

Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication), use Redshift for efficient loading strategies and write ETL pipelines that handle large volumes of data efficiently, with low latency. Location/WFH: You'll join a small but growing team More ❯

Proficiency in data analysis using Pandas, Numpy, SciPy etc. Experience with object oriented design, distributed systems architecture, performance tuning. Experience with designing and programming relational database such as MySQL, RedShift, Oracle SQL Server, or Postgres. Experience with AWS based system architecture covering S3, EKS, EC2, Batch, or Airflow etc. Experience with caching and messaging technologies such as, Redis, Hazelcast More ❯

structured and unstructured data using Python, R, SQL, AWS services and other tools. Build and maintain data repositories using AWS S3 and FSx technologies. Establish data warehousing solutions using Amazon Redshift. Build and maintain standard data models. Own data quality frameworks, validation processes and KPIs to ensure accuracy and consistency of data pipelines. Implement data versioning and lineage tracking … R&D. Required Knowledge, Skills and Abilities Expert knowledge of data engineering tools such as Python, R and SQL for data processing. Expert proficiency with AWS services particularly S3, Redshift, FSx, Glue, Lambda. Expert proficiency with relational databases. Strong background in data modeling and database design. Strong knowledge with unstructured database technologies (e.g. NoSQL) and other database types (e.g. More ❯

management . 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 More ❯

management . 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 More ❯

Strong stakeholder management and communication skills, with the ability to translate technical outputs into business-friendly insights. Experience with Snowflake (or alternative cloud data warehouses such as BigQuery or Redshift). Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we have built, and we welcome applications from people More ❯

and creating/executing tests Requirements Strong experience as a Data Engineer (migrating legacy systems onto AWS, building data pipelines) Strong Python experience Tech stack experience required: AWS Glue, Redshift, Lambda, PySpark, Airflow SSIS or SAS experience (Desirable) Benefits Salary up to £57,500 + up to 20% bonus Hybrid working: 1 to 2 days a week in the More ❯

most appropriate technologies, deploying final implementations on AWS. You'll bring hands-on depth and knowledge in: Languages: Python, PySpark, SQL Technologies: Spark, Airflow Cloud: AWS (API Gateway, Lambda, Redshift, Glue, CloudWatch, etc.) Data Pipelines: Designing and building modern, cloud-native pipelines using AWS services In addition, you will require strong leadership skills and excellent communication abilities, with the More ❯

optimization skills. Excellent problem-solving and analytical skills. Good to Have: Knowledge of Python/PySpark for big data solutions. Experience with AWS cloud services (S3, Glue, Athena, EMR, Redshift Mandatory Skills: Ab Initio (link removed) Experience: 5-8 Years (link removed) The expected compensation for this role ranges from $60,000 to $135,000 (link removed) Final compensation More ❯

learning, reinforcement learning, LLM orchestration, RAG systems, etc Familiarity with cloud services and MLOps tooling to deploy and scale data and ML workloads cost-effectively Familiarity with data warehouses (Redshift, BigQuery, Snowflake, etc) and best practices around data pipeline tools Strong proficiency in SQL Comfort with ambiguity and short feedback loops A passion for building products that make a More ❯