Bytes is a top provider of premium IT solutions and services, working with SMEs, corporations, and public sector organizations to modernize and digitally transform their IT infrastructures. Founded in 1982, Bytes has experienced significant growth, now employing over 750 people across seven locations in the UK and Ireland, with a turnover surpassing £1.8 billion in 2023.
At Bytes, we nurture talented individuals to achieve remarkable outcomes and are dedicated to supporting our employees through continuous training, guidance, and development to help you advance and fulfil your career goals. We foster a culture of innovation, collaboration, recognition and inclusivity and offer a wide range of benefits to support staff wellbeing.
Operating from modern, hybrid working environments with offices in Leatherhead, Reading, London and Manchester
25 days holiday per annum plus bank holidays and Christmas period
Excellent learning and development opportunities
Open plan office with collaborative working spaces, on-site gym, outdoor tiki bar, coffee bar, and lunch area
Company wellbeing and social events
Sports and social clubs
Incentive trips
Employee Assistance Programme
Discounted private healthcare
EV scheme and Ride to Work scheme
Winners of an array of industry awards
Great Place to Work Certified
Sunday Times Top 100 Best Places to Work
Supporters of 85+ charities with strong commitment to diversity and sustainability
POSITION DETAILS:
Position Title:
Data Warehouse Developer Reports to (POSITION):
Database Manager Team:
Systems Development Department:
Services & Solutions PURPOSE OF JOB:
We are looking for an experienced Data Warehouse Developer with 2-5 years of experience to design, develop, and optimize data warehousing solutions. The ideal candidate will be proficient in building and maintaining data warehouses and ETL processes, with some exposure to modern data lake technologies. You will work closely with our internal development teams/Infra team to ensure data integrity, performance, and availability of Datawarehouse environment for reporting and analysis purposes. KEY RESPONSIBILITIES:
Design, Develop, and Maintain Data Warehouses: Design and implement data warehouse architectures that support enterprise reporting, analytics, and business intelligence. Develop, optimize, and manage ETL (Extract, Transform, Load) processes to integrate data from multiple sources into the data warehouse. Create and manage data models, schemas, and dimensional models (e.g., star, snowflake schemas) for efficient data storage and retrieval. Data Integration & Transformation: Work with relational databases such as SQL Server, Oracle, PostgreSQL, and integrate data from diverse sources such as flat files, APIs, or cloud services. Write complex SQL queries and stored procedures to transform raw data into structured formats for reporting and analysis. Implement and support ETL pipelines using tools such as SSIS, Informatica, or Azure Data Factory Data Governance & Quality: Ensure the accuracy, consistency, and reliability of data across the warehouse. Develop and implement data validation, cleansing, and transformation processes to ensure high data quality. Support data governance initiatives by documenting data structures, data flows, and maintaining metadata. Exposure to Data Lake Technologies: Exposure to Data Lake environments such as Azure Data Lake, AWS S3, or Google Cloud Storage to support semi-structured and unstructured data ingestion. Knowledge on how to manage data flows between data lakes and data warehouses, ensuring data is accessible for reporting and analysis when needed. Performance Monitoring & Optimization: Monitor and troubleshoot data warehouse performance, optimizing for query efficiency and storage. Ensure optimal database performance by implementing indexing, partitioning, and performance-tuning techniques. Collaborate with the Infra/Support team to ensure data systems are highly available, scalable, and secure. QUALIFICATIONS, EXPERIENCE, & SKILLS: Educational Qualifications: Bachelor’s degree in computer science, Information Systems, or related field. Years of Experience 3-5 years of experience in Data Warehouse development, design, and management. Core Competencies & Skills: Exposure to data lake technologies (e.g., Azure Data Lake, AWS S3) and an understanding of their use in data management and architecture (experience with them is a plus, but not required). Experience with cloud-based data platforms such as Azure Synapse Analytics, AWS Redshift, or Google BigQuery is a plus. Familiarity with data warehousing methodologies (e.g., Kimball, Inmon), dimensional modelling, and schema design. Strong SQL programming skills, including writing complex queries, stored procedures, and query performance tuning. Proficiency with SQL and relational databases such as SQL Server, Oracle, PostgreSQL, or MySQL. Familiarity with Big Data tools like Apache Spark, Hadoop, or Databricks is an added advantage. Experience working in an Agile environment with DevOps practices and CI/CD pipeline management for data integration. Experience in cloud migration or hybrid data architectures combining on-premise and cloud data solutions.
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Data Warehouse Developer Reports to (POSITION):
Database Manager Team:
Systems Development Department:
Services & Solutions PURPOSE OF JOB:
We are looking for an experienced Data Warehouse Developer with 2-5 years of experience to design, develop, and optimize data warehousing solutions. The ideal candidate will be proficient in building and maintaining data warehouses and ETL processes, with some exposure to modern data lake technologies. You will work closely with our internal development teams/Infra team to ensure data integrity, performance, and availability of Datawarehouse environment for reporting and analysis purposes. KEY RESPONSIBILITIES:
Design, Develop, and Maintain Data Warehouses: Design and implement data warehouse architectures that support enterprise reporting, analytics, and business intelligence. Develop, optimize, and manage ETL (Extract, Transform, Load) processes to integrate data from multiple sources into the data warehouse. Create and manage data models, schemas, and dimensional models (e.g., star, snowflake schemas) for efficient data storage and retrieval. Data Integration & Transformation: Work with relational databases such as SQL Server, Oracle, PostgreSQL, and integrate data from diverse sources such as flat files, APIs, or cloud services. Write complex SQL queries and stored procedures to transform raw data into structured formats for reporting and analysis. Implement and support ETL pipelines using tools such as SSIS, Informatica, or Azure Data Factory Data Governance & Quality: Ensure the accuracy, consistency, and reliability of data across the warehouse. Develop and implement data validation, cleansing, and transformation processes to ensure high data quality. Support data governance initiatives by documenting data structures, data flows, and maintaining metadata. Exposure to Data Lake Technologies: Exposure to Data Lake environments such as Azure Data Lake, AWS S3, or Google Cloud Storage to support semi-structured and unstructured data ingestion. Knowledge on how to manage data flows between data lakes and data warehouses, ensuring data is accessible for reporting and analysis when needed. Performance Monitoring & Optimization: Monitor and troubleshoot data warehouse performance, optimizing for query efficiency and storage. Ensure optimal database performance by implementing indexing, partitioning, and performance-tuning techniques. Collaborate with the Infra/Support team to ensure data systems are highly available, scalable, and secure. QUALIFICATIONS, EXPERIENCE, & SKILLS: Educational Qualifications: Bachelor’s degree in computer science, Information Systems, or related field. Years of Experience 3-5 years of experience in Data Warehouse development, design, and management. Core Competencies & Skills: Exposure to data lake technologies (e.g., Azure Data Lake, AWS S3) and an understanding of their use in data management and architecture (experience with them is a plus, but not required). Experience with cloud-based data platforms such as Azure Synapse Analytics, AWS Redshift, or Google BigQuery is a plus. Familiarity with data warehousing methodologies (e.g., Kimball, Inmon), dimensional modelling, and schema design. Strong SQL programming skills, including writing complex queries, stored procedures, and query performance tuning. Proficiency with SQL and relational databases such as SQL Server, Oracle, PostgreSQL, or MySQL. Familiarity with Big Data tools like Apache Spark, Hadoop, or Databricks is an added advantage. Experience working in an Agile environment with DevOps practices and CI/CD pipeline management for data integration. Experience in cloud migration or hybrid data architectures combining on-premise and cloud data solutions.
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