51 to 75 of 172 Permanent Amazon Redshift Jobs

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 ❯

/BI Engineering experience Excellent SQL skills Understanding of data warehousing, data modelling concepts and structuring new data tables Knowledge of cloud-based MPP data warehousing (e.g. Snowflake, BigQuery, Redshift) Nice to have Experience developing in a BI tool (Looker or similar) Good practical understanding of version control SQL ETL/ELT knowledge, experience with DAGs to manage script More ❯

Python and related ML libraries Strong background in applied machine learning, model development and data engineering Experience with cloud environments (Azure, AWS, GCP) and tools such as Spark, Hive, Redshift Demonstrated ability to lead cross-functional teams and mentor junior practitioners Ability to communicate complex technical concepts clearly to non-technical audiences Bonus Points For Participation in Kaggle or More ❯

acceptable) Working knowledge of SQL and data modelling concepts Experience with BI tools (e.g., Power BI, Looker, Tableau) Familiarity with cloud data platforms such as Snowflake, BigQuery, or AWS Redshift Understanding of modern data architecture and APIs Our Offer Flexi-Week and Work-Life Balance: We prioritise your mental health and wellbeing, offering you a flexible four-day Flexi More ❯

quality and reliability in the organization Qualifications Understanding of data engineering (including SQL, Python, Data Warehousing, ETL, Dimensional Modelling, Analytics) Understanding of cloud data infrastructure elements, and ideally AWS (Redshift, Glue, Athena, S3) and understanding of existing governance frameworks of data quality and their dimensions (DAMA, GOV.UK, etc.). Experience in Exploratory Testing, automation experience, and time and attention More ❯

alongside the ability to upskill team members through peer review, training, and best practice development. Data Infrastructure: A solid understanding of cloud-based data warehousing (e.g., Azure, Fabric, Snowflake, Redshift, BigQuery) and ETL processes. Analytical Prowess: Exceptional analytical and problem-solving skills, with the ability to translate complex data into clear, actionable business insights. Demonstrated proficiency in Python/ More ❯

improve our technology stack. Develop oneself into a Subject Matter Expert (SME) on Technical and Functional domain areas. What we value Demonstrated experience in Python, PySpark and SQL (AWS Redshift, Postgres, Oracle). Demonstrated experience building data pipelines with PySpark and AWS. Application development experience in financial services with hands on designing, developing, and deploying complex applications.Demonstrated ability to More ❯

greater efficiency and impact. The skills you'll need to succeed Leadership in data engineering and Agile delivery Advanced knowledge of AWS data services (e.g. S3, Glue, EMR, Lambda, Redshift) Expertise in big data technologies and distributed systems Strong coding and optimisation skills (e.g. Python, Spark, SQL) Data quality management and observability Strategic thinking and solution architecture Stakeholder and More ❯

consolidated insights—ensuring data is accurate, accessible, and actionable. Architect Scalable Data Solutions: Design and implement enterprise-grade data pipelines and architectures using AWS services (e.g. S3, Glue, Lambda, Redshift, EMR, Kinesis), optimised for analytics and scalability. Set Technical Direction: Define and guide technical decisions related to data conceptualisation, modelling, and visualisation within the organisation’s analytics ecosystem. Champion More ❯

consolidated insights-ensuring data is accurate, accessible, and actionable. Architect Scalable Data Solutions: Design and implement enterprise-grade data pipelines and architectures using AWS services (e.g. S3, Glue, Lambda, Redshift, EMR, Kinesis), optimised for analytics and scalability. Set Technical Direction: Define and guide technical decisions related to data conceptualisation, modelling, and visualisation within the organisation's analytics ecosystem. Champion More ❯

Mentor junior consultants Build strong customer relationships Support managed services as required Essential Requirements 3+ years consulting/managed services experience Solid Data Lake experience with AWS data solutions (Redshift, Glue, Athena, Lake Formation) Advanced AWS skills (EC2, S3, VPC, IAM, Lambda) Infrastructure as Code experience (CloudFormation/Terraform) AWS Solutions Architect Associate certification Strong communication and presentation abilities More ❯

CSS, Bootstrap/Reactstrap, and JavaScript frameworks such as React Experience with data warehousing technologies Familiarity with cloud platforms including AWS and/or Google Cloud Platform (e.g., BigQuery, Redshift) Exceptional written and verbal communication skills, including the ability to convey technical concepts to non-technical stakeholders Proficiency in technical writing and editing using Microsoft Office tools (Excel, Word More ❯

data-focused SRE, Data Platform, or DevOps role Strong knowledge of Apache Flink, Kafka, and Python in production environments Hands-on AWS experience with AWS (Lambda, EMR, Step Functions, Redshift, etc.) Comfortable with monitoring tools, distributed systems debugging, and incident response Reference Number: BBBH259303 To apply for this role or for to be considered for further roles, please click More ❯

data-focused SRE, Data Platform, or DevOps role *Strong knowledge of Apache Flink, Kafka, and Python in production environments *Hands-on AWS experience with AWS (Lambda, EMR, Step Functions, Redshift, etc.) *Comfortable with monitoring tools, distributed systems debugging, and incident response Reference Number: BBBH259303 To apply for this role or for to be considered for further roles, please click More ❯

data-focused SRE, Data Platform, or DevOps role*Strong knowledge of Apache Flink, Kafka, and Python in production environments*Hands-on AWS experience with AWS (Lambda, EMR, Step Functions, Redshift, etc.)*Comfortable with monitoring tools, distributed systems debugging, and incident response Reference Number: BBBH259303 To apply for this role or for to be considered for further roles, please click More ❯

production data systems. Advanced SQL skills and deep experience implementing complex business logic and performance-optimized transformations at scale. Expertise with modern cloud-based data platforms (e.g., Snowflake, BigQuery, Redshift) and experience managing large, distributed data environments. Strong understanding of data architecture and dimensional modeling principles, with a track record of designing enterprise-grade schemas. Proven ability to lead More ❯

drills for stream and batch environments. Architecture & Automation Collaborate with data engineering and product teams to architect scalable, fault-tolerant pipelines using AWS services (e.g., Step Functions , EMR , Lambda , Redshift ) integrated with Apache Flink and Kafka . Troubleshoot & Maintain Python -based applications. Harden CI/CD for data jobs: implement automated testing of data schemas, versioned Flink jobs, and More ❯

communicator - able to engage with both technical and non-technical colleagues. Nice to Have Skills Experience working with GCP (BigQuery) or other modern cloud-native data warehouses (e.g. Snowflake, Redshift). Familiarity with data pipelining and orchestration systems (e.g. Airflow). Understanding of modern analytics architectures and data visualisation tools (we use Preset.io/Apache Superset). Exposure to More ❯

communicator - able to engage with both technical and non-technical colleagues. Nice to Have Skills Experience working with GCP (BigQuery) or other modern cloud-native data warehouses (e.g. Snowflake, Redshift). Familiarity with data pipelining and orchestration systems (e.g. Airflow). Understanding of modern analytics architectures and data visualisation tools (we use Preset.io/Apache Superset). Exposure to More ❯

hypothesis testing, regression, significance, p-value pitfalls) Ability to translate data into plain-English insights and present to C-level audiences Experience working in cloud data warehouses (Snowflake, BigQuery, Redshift) and version control (Git) What we can offer Bonus Hybrid working; meaning you'll be in our Farringdon office Tuesdays to Thursdays 25 days annual leave, plus the Bank More ❯

to-end data flow diagrams, logical data models, and entity relationship diagrams (ERDs). Design scalable, secure, and robust data architectures on AWS, incorporating services such as S3, Glue, Redshift, RDS, and Lambda. Work with stakeholders to understand business and data requirements and translate them into architectural blueprints. Ensure data architecture complies with government standards for security, interoperability, and More ❯

to-end data flow diagrams, logical data models, and entity relationship diagrams (ERDs). Design scalable, secure, and robust data architectures on AWS, incorporating services such as S3, Glue, Redshift, RDS, and Lambda. Work with stakeholders to understand business and data requirements and translate them into architectural blueprints. Ensure data architecture complies with government standards for security, interoperability, and More ❯

lead on career development opportunities Ability to evangelize next-generation infrastructure in analytics space (batch, near real-time, real-time technologies), using both SAS components and AWS tooling (e.g., Redshift, SQS, Kinesis) Strong familiarity with spatial-temporal data sets, with exposure to maritime data preferred Experienced in evaluating, training, and communicating the performance of ML models (e.g., supervised models More ❯

analytical and problem-solving skills with the ability to interpret complex data and investment processes. Proficiency in: SQL - for data validation and exploration. AWS - particularly data services (e.g., S3, Redshift, Lambda). Python - for prototyping analytical tools and performing data analysis. Strong command of business analysis practices, including: Use case and workflow documentation Data mapping and transformation Acceptance criteria More ❯

to-end data flow diagrams, logical data models, and entity relationship diagrams (ERDs). Design scalable, secure, and robust data architectures on AWS, incorporating services such as S3, Glue, Redshift, RDS, and Lambda. Work with stakeholders to understand business and data requirements and translate them into architectural blueprints. Ensure data architecture complies with government standards for security, interoperability, and More ❯