Senior Data Engineer

DEPARTMENT:

Enterprise Data

LOCATION:

One New Change, London, EC4M 9AF

SHIFT PATTERN:

Monday to Friday, 09:00-17:30 - Hybrid working (3 days in Office per week)

RESPONSIBLE FOR:

Leading (and carrying out) Data Engineering activities for and not limited to the Data Platforms and Services

BACKGROUND:

CDW is a leading technology solutions provider to business, government, education and healthcare organisations in the United Kingdom, Canada, and the United States. Our fingerprints can be found on technology in workplaces of more than 250,000 companies: from start-ups to international conglomerates. With the breadth of products and services we offer, there is no request too big or too small.

CDW prides itself on being ‘People Who Get IT’ and ‘People who get People’. Our relationships are fuelled by our deep expertise and grounded in the CDW Way. Our empowering leadership makes things happen and inspires their teams to do the same. From the teammates beside us to the leaders who guide us, we move forward together. At CDW, you’ll work with people who inspire you. People with positive, success-driven attitudes who you will learn from and forge strong relationships with. Bring your best true self—and your best ideas—to CDW. Because diverse perspectives bring forth better problem solving—and better solutions for our customers on a rapidly evolving technology landscape.

KEY DUTIES:

CDW is constantly evolving our Data and technology landscape and are looking for a Senior Data Engineer to join a growing team to ingest, cleanse and model data into single source of truth, Kimball datasets, used for Business Intelligence reporting, ML, DS & AI and more. A Senior Data Engineer to manage, lead, guide, advice and develop technology and people. Responsible to lead the work, activities, oversight and management of Data Engineers reporting into this role. Design and develop homogenous data repositories to deliver data led decision making. Ingest data from various sources, including on premise SQL databases, REST API’s, Apache Kafka streams, etc. Define and apply cleansing rules to the data to ensure meets quality expectations. Define and model data for its appropriate use including into single source of truth Kimball datasets, e.g. dimensions and facts. DevOps approach to software; create high quality code using traditional software practices, such as building, linting, unit and integration testing, repositories, CI/CD, peer reviews, etc. DevOps approach to support; monitor pipelines to ensure business-critical data pipelines are processed meeting time constraint and data quality expectations (including implementing reactive changes where applicable). Drive and Integrate into the data team’s WOW, including backlog refinement, sprint planning, demonstrations, and retrospectives, including translation of user requirements into technical requirements including complexity estimation, implement into sprint cycles, collaboration into process improvement, etc. Based on requirements, perform ad-hoc analysis of structured and unstructured data across multiple data sources to inform solution design. Document datasets in data catalogue, including ownership, stewardship, dictionaries, glossaries, lineage, sensitivity, etc. Ownership of Work Items and works with data owners / stewards to ensure high quality, aligned deliveries, and compliance with legislation, such as GDPR, e.g. PII vs Non-PII, data retention, etc. Document solution design inline with Data Governance. Support all data platforms and ensure its smooth running. Ad-hoc Analysis: Perform ad-hoc analysis of structured and unstructured data to inform solution design and support decision-making processes.