Hybrid

Department:

Sitting within Product & Technology, Enterprise Data Services (EDS) is responsible for providing data, reporting, integration, process automation and CRM capabilities across Cox Automotive Europe. We own the data and business platforms, design and develop reusable enterprise data assets, and drive best practices to support adoption and effective utilisation of the shared enterprise data capabilities.

Job Role:

As an Analytics Engineer you will be working on creating and maintaining high quality reusable data assets for both internal and external use cases. You will work closely with business stakeholders to understand their data needs, build data pipelines to source and model the required data and support the data assets you create from operational perspective – monitor data pipeline runs, fix any issues, develop enhancements and optimisations.

You will be the go-to expert for complex data questions across the business areas you support. You will proactively engage your colleagues and wider stakeholder community around what data is available and how to use it to answer specific business questions. As well as focusing on data content, you will support wider Enterprise Data Services team with defining, implementing, and championing best practices around data asset creation and management (quality, cataloguing, lineage, access management, etc.).

While your main focus will be on our internal data you will also support managing 3^rd party data assets. You will maintain visibility of what is used where, provide internal expertise around this data, and liaise with 3^rd party providers on all technical data integration matters for the areas you support.

You will have plenty of opportunities step out of your specific role and get hands on with managing elements of data and reporting platforms and learn the Data Engineering craft.

You will contribute to EDS strategy and roadmaps. You will constantly look out for improvements to existing and highlight opportunities for new data platform capabilities.

Data Asset Development and Maintenance

• Work with stakeholders to capture requirements, prototype, ingest and model new data as well as enhance existing data products.
• Manage data mapping documents which contain source database information and rename fields to report friendly names to be used in report databases. Outline all calculated fields which will be required for reporting on the data.
• Design, develop, test, document and deploy data pipeline code. Work with Data Engineering team to design new approaches for new data sources and data processing requirements.
• Ensure all projects conform to and champion best practice data modelling and management patterns.
• Review existing data integration solutions to see whether improvements can be made, weighing up the cost of changing the existing solution against perceived benefits.
• Monitor and support data pipelines from operational perspective. Troubleshoot any issues, provide fixes where possible, escalate to other teams where appropriate.

Data Management

• Create and maintain detailed data documentation with data from across the business outlining what data is contained within databases at table and field level, providing context into fields and outlining what data fields contain private data.
• Establish common approaches to managing data within GDPR requirements framework – providing transparency around what is being captured and processed and how, data retention management, data access control.
• Oversee, drive, and champion data quality management process for all data assets owned and managed by Enterprise Data Assets.
• Produce best practice documentation on creating data products capitalising on our internal development frameworks as well as wider data platform capabilities. Cover everything from coding and design guidelines, solution blueprints and common patterns to development workflows and tooling.
• Work with wider teams to proactively seek out new opportunities to utilise EDS technology and drive wider adoption of available data assets.

Project Delivery

• Be responsible for leading the delivery of multiple Data Engineering development projects at a time.
• Be responsible for managing priorities and technical resourcing within those projects, and for stakeholder management and engagement around delivery and project updates.

Stakeholder Management

• Act as a point of contact for data integration questions and work with both technical and non-technical stakeholders from the project inception to final implementation to offer technological steer and design, develop and maintain appropriate solutions.
• Work with the relevant technology teams to ensure all technical prerequisites for integration work are met and use your influence to remove any major blockers.
• Act as the point of contact for all questions for projects you are leading and manage the communication and expectations around the project development lifecycle to all stakeholders in the business that are engaged with the project.
• Be responsible for managing communications and questions about our data assets and engage with both technical and non-technical stakeholders who may require access or information about these.

Platform Administration

• Support day to day management of Data Services platforms, set up users, investigate security issues and ensure general availability of the platform. Escalate issues to internal technology teams and vendors as appropriate.

Strategy

• Be a major contributor to EDS strategy and roadmaps – closely follow the industry trends and suggest new system designs to exploit emerging technologies.
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Skills & Knowledge – Technical Skills

• Strong requirements gathering skills and ability to turn the requirements into elegant technical solutions.
• Solid knowledge of data modelling, experience working with different data sources and using different data integration approaches.
• Practical data management expertise covering aspects like data cataloguing, data lineage, and data quality.
• Working knowledge of modern data platforms like Databricks/Snowflake as well as more general data tooling offered by the public cloud providers like AWS, Azure, or GCP.
• Tableau / PowerBI with focus on effective and efficient data model development.
• Advanced SQL skills – familiarity with concepts like window functions, UDFs, nested data structures, etc.
• Good understanding software development lifecycle (SDLC) concepts like multiple environments, version control, build pipelines.
• Exposure to Python and PySpark development highly advantageous.

Skills & Knowledge – Interpersonal and Non-Technical Skills

• A strong natural focus on what matters; delivering value and designing to minimise risk. Ready to roll up your sleeves and get stuck in, both with project work as well as team and community activities.
• The ability to work across multiple projects in parallel and the ability to contribute to wider group strategies.

• Hands-on experience of working through the end-to-end project lifecycle with exposure to both Waterfall and Agile methodologies
• Self-motivated individual with great attention to detail who can investigate issues with little information and find a solution.

• Excellent interpersonal skills, verbal and written communication skills when working with both business and technical teams.
• Be able to train team members and business users of varying technical knowledge.

STRICTLY NO AGENCIES PLEASE:

We work with a carefully selected set of recruitment agencies and we're not looking to add to our PSL.

We do not accept unsolicited agency CV's sent to the recruitment team or directly to the hiring manager. We will not be responsible for any fees related to unsolicited CV's

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