Data Delivery Analyst

​​POSITION DESCRIPTION:

• Working within the Data and Analytics Solutions team within Ford Credit Europe, candidate will be responsible for working with internal customers, Data Engineering, and Architecture to ingest data, create pipelines, and facilitate customer reporting from the company’s Google Cloud Platform Data Warehouse.

Skills Required:

Technical Skills

• SQL: Advanced proficiency in SQL for complex queries, data transformations, and performance optimization

• Python: Strong Python skills for data manipulation, analysis, and automation scripts

• Looker: Hands-on experience with Looker and LookML

• Power BI: Proficiency in Power BI for business intelligence and reporting solutions

• GCP: Familiarity with Google Cloud Platform data services and tools

• AI/ML Tools: Basic exposure to AI/ML concepts and willingness to learn tools like BigQuery ML, AutoML, or other GCP AI service

Data Management Skills

• Semantic Modeling: Understanding of semantic layer concepts, business definitions, and logical data modeling

• Data Quality: Knowledge of data validation, cleansing, and quality assurance processes

• Business Intelligence: Experience creating self-service analytics and reporting solutions

• Data Analysis: Ability to analyze complex datasets and translate findings into business insights

Business & Communication Skills

• Requirements Gathering: Ability to work with business stakeholders to understand and document data needs

• Stakeholder Management: Effective communication across technical and business teams

• Problem-Solving: Systematic approach to resolving data-related business challenges

• Training & Support: Capability to provide guidance and training to business users

• Cloud Data Warehousing: Knowledge of BigQuery and cloud-based data storage solutions

• Version Control: Experience with Git for managing code experience required; Experience working within a data function or supporting data through engineering work or business projects. Refer to detailed skills requirements to guide on experience needed.

Professional Attributes

• Collaboration: Strong partnership skills for working with Data Engineering, Architecture, Governance teams

• Analytical Mindset: Logical approach to data modeling and semantic layer design

• Continuous Learning: Interest in emerging data technologies and AI applications in banking

• Attention to Detail: Critical for maintaining data accuracy in regulated environments

• Agile Methodologies: managing own work and managing roadmaps with key stakeholders