26 to 50 of 695 Permanent Amazon Redshift Jobs

cloud technologies for ETL pipeline, data warehouse and data lake design/building and data movement. AWS data and analytics services (or open-source equivalent) such as EMR, Glue, RedShift, Kinesis, Lambda, DynamoDB. What you can expect Work to agile best practices and cross-functionally with multiple teams and stakeholders. You’ll be using your technical skills to problem More ❯

cloud technologies for ETL pipeline, data warehouse and data lake design/building and data movement. AWS data and analytics services (or open-source equivalent) such as EMR, Glue, RedShift, Kinesis, Lambda, DynamoDB. What you can expect Work to agile best practices and cross-functionally with multiple teams and stakeholders. You’ll be using your technical skills to problem More ❯

Familiarity with ETL tools and big data platforms. Knowledge of data modelling, replication, and query optimization. Experience with SQL and NoSQL databases. Exposure to data warehousing tools (e.g., Snowflake, Redshift, BigQuery). Data Platform Management Experience in hybrid environments (cloud/on-prem). Skilled in integrating diverse data sources. Understanding of secure data transfer and disaster recovery planning. More ❯

team of highly technically skilled engineers, who are enhancing Creditsafe’s data offerings with high throughput and scalability as primary goals. The data delivery platform is built upon AWS Redshift and S3 cloud storage. The platform manages billions of objects, with daily increments in the 10s of millions. Our ETL processes are built in Python and Rust, efficiently transforming More ❯

Core Skills Cloud Expertise: Azure, AWS, SAP Data Engineering: ELT/ETL, Data Modeling, Data Warehousing Tools & Tech: Azure Data Factory, Databricks, Synapse, Stream Analytics, AWS Glue, Airflow, Kinesis, Redshift, SQL, GitHub, Azure DevOps, SonarQube, PyTest Preferred Experience Leading agile or scrum-based technical teams. Working with financial or planning data. Using documentation tools (e.g., MKDocs ). Why You More ❯

Core Skills Cloud Expertise: Azure, AWS, SAP Data Engineering: ELT/ETL, Data Modeling, Data Warehousing Tools & Tech: Azure Data Factory, Databricks, Synapse, Stream Analytics, AWS Glue, Airflow, Kinesis, Redshift, SQL, GitHub, Azure DevOps, SonarQube, PyTest Preferred Experience Leading agile or scrum-based technical teams. Working with financial or planning data. Using documentation tools (e.g., MKDocs ). Why You 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 ❯

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 ❯

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 ❯

Governance, Security & Compliance - aligned to Data best practices. Liaison with IT Business Systems & Business Teams & Third Parties. Drive Continuous Improvement. Technical Skills Required: Azure Data Factory. 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 More ❯

Key Skills & Experience: Proven experience as a Senior Data Engineer in a large-scale or complex environment. Strong hands-on expertise with AWS data services (e.g., S3, Glue, Lambda, Redshift, Athena, EMR). Experience building data lakes and modern data platforms from the ground up. Proficiency with Python, SQL, and orchestration tools such as Airflow or dbt. Strong understanding 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

as testing, version control, and CI/CD Hands-on experience building scalable data pipelines in a modern cloud environment (e.g., dbt, AWS Glue, AWS Lake Formation, Apache Spark, Amazon Redshift) Strong understanding of data modeling, ELT design patterns, data governance, and security best practices Bonus . Experience with reverse ETL tools (e.g., Census) Knowledge of data privacy More ❯

as testing, version control, and CI/CD Hands-on experience building scalable data pipelines in a modern cloud environment (e.g., dbt, AWS Glue, AWS Lake Formation, Apache Spark, Amazon Redshift) Strong understanding of data modeling, ELT design patterns, data governance, and security best practices Bonus . Experience with reverse ETL tools (e.g., Census) Knowledge of data privacy More ❯

as testing, version control, and CI/CD Hands-on experience building scalable data pipelines in a modern cloud environment (e.g., dbt, AWS Glue, AWS Lake Formation, Apache Spark, Amazon Redshift) Strong understanding of data modeling, ELT design patterns, data governance, and security best practices Bonus . Experience with reverse ETL tools (e.g., Census) Knowledge of data privacy More ❯

or analytics engineering, ideally within fintech, SaaS, or digital platforms Deep proficiency in SQL and hands-on experience with dbt Experience working with modern data warehouses (Snowflake, BigQuery, or Redshift) Familiarity with software engineering principles (Git, CI/CD, testing frameworks) Strong understanding of data visualisation and BI tools Confident communicator able to translate technical detail into clear business More ❯

or analytics engineering, ideally within fintech, SaaS, or digital platforms Deep proficiency in SQL and hands-on experience with dbt Experience working with modern data warehouses (Snowflake, BigQuery, or Redshift) Familiarity with software engineering principles (Git, CI/CD, testing frameworks) Strong understanding of data visualisation and BI tools Confident communicator able to translate technical detail into clear business More ❯

or analytics engineering, ideally within fintech, SaaS, or digital platforms Deep proficiency in SQL and hands-on experience with dbt Experience working with modern data warehouses (Snowflake, BigQuery, or Redshift) Familiarity with software engineering principles (Git, CI/CD, testing frameworks) Strong understanding of data visualisation and BI tools Confident communicator able to translate technical detail into clear business More ❯

or analytics engineering, ideally within fintech, SaaS, or digital platforms Deep proficiency in SQL and hands-on experience with dbt Experience working with modern data warehouses (Snowflake, BigQuery, or Redshift) Familiarity with software engineering principles (Git, CI/CD, testing frameworks) Strong understanding of data visualisation and BI tools Confident communicator able to translate technical detail into clear business More ❯

or analytics engineering, ideally within fintech, SaaS, or digital platforms Deep proficiency in SQL and hands-on experience with dbt Experience working with modern data warehouses (Snowflake, BigQuery, or Redshift) Familiarity with software engineering principles (Git, CI/CD, testing frameworks) Strong understanding of data visualisation and BI tools Confident communicator able to translate technical detail into clear business More ❯