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For Companies At a Glance
- Tasks: Design and build data pipelines for advanced analytics and AI-driven solutions.
- Company: Join EY, a global leader in consulting and technology innovation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Make an impact by transforming businesses with cutting-edge data engineering.
- Qualifications: Degree in a relevant field and experience with data engineering tools.
- Other info: Collaborative environment with diverse projects across various industries.
The predicted salary is between 43200 - 72000 £ per year.
We are seeking a highly skilled Data Engineer Senior Consultant with hands-on experience designing, building, and optimizing data solutions that enable advanced analytics and AI-driven business transformation. This role requires expertise in modern data engineering practices, cloud platforms, and the ability to deliver robust, scalable data pipelines for diverse business domains such as finance, supply chain, energy, and commercial operations.
Your Client Impact
- Design, develop, and deploy end-to-end data pipelines for complex business problems, supporting analytics, modernising data infrastructure and AI/ML initiatives.
- Design and implement data models, ETL/ELT workflows, and data integration solutions across structured and unstructured sources.
- Collaborate with AI engineers, data scientists, and business analysts to deliver integrated solutions that unlock business value.
- Ensure data quality, integrity, and governance throughout the data lifecycle.
- Optimize data storage, retrieval, and processing for performance and scalability on cloud platforms (Azure, AWS, GCP, Databricks, Snowflake).
- Translate business requirements into technical data engineering solutions, including architecture decisions and technology selection.
- Contribute to proposals, technical assessments, and internal knowledge sharing.
- Data preparation, feature engineering, and MLOps activities to collaborate with AI engineers, data scientists, and business analysts to deliver integrated solutions.
Essential Qualifications
- Degree or equivalent certification in Computer Science, Data Engineering, Information Systems, Mathematics, or related quantitative field.
Essential Criteria
- Proven experience building and maintaining large-scale data pipelines using tools such as Databricks, Azure Data Factory, Snowflake, or similar.
- Strong programming skills in Python and SQL, with proficiency in data engineering libraries (pandas, PySpark, dbt).
- Deep understanding of data modelling, ETL/ELT processes, and Lakehouse concepts.
- Experience with data quality frameworks, data governance, and compliance requirements.
- Familiarity with version control (Git), CI/CD pipelines, and workflow orchestration tools (Airflow, Prefect).
Soft Skills
- Strong analytical and problem-solving mindset with attention to detail.
- Good team player with effective communication and storytelling with data and insights.
- Consulting skills, including development of presentation decks and client-facing documentation.
Preferred Criteria
- Experience with real-time data processing (Kafka, Kinesis, Azure Event Hub).
- Knowledge of big data storage solutions (Delta Lake, Parquet, Avro).
- Experience with data visualization tools (Power BI, Tableau, Looker).
- Understanding of AI/ML concepts and collaboration with AI teams.
Preferred Qualifications
- Certifications such as:
- Databricks Certified Data Engineer Professional
- Azure Data Engineer Associate
- AWS Certified Data Analytics – Specialty
- SnowPro Advanced: Data Engineer
Senior Consultant, Data Engineer, AI&Data, UKI, London employer: EY
Contact Detail:
EY Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Consultant, Data Engineer, AI&Data, UKI, London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with professionals on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving cloud platforms and data pipelines. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as communication is key in consulting roles. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Consultant, Data Engineer, AI&Data, UKI, London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Data Engineer Senior Consultant. Highlight your experience with data pipelines, cloud platforms, and any relevant projects that showcase your skills in AI and analytics.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data engineering and how your background aligns with our needs. Be specific about your achievements and how they relate to the job description.
Showcase Your Technical Skills: Don’t hold back on your technical prowess! Clearly list your programming skills, tools you’ve used like Databricks or Snowflake, and any certifications you have. We want to see what makes you stand out as a candidate.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensure it gets the attention it deserves!
How to prepare for a job interview at EY
✨Know Your Data Engineering Tools
Make sure you’re well-versed in the tools mentioned in the job description, like Databricks, Azure Data Factory, and Snowflake. Brush up on your Python and SQL skills, and be ready to discuss how you've used these tools to build and maintain data pipelines in your previous roles.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of complex business problems you've solved using data engineering. Think about how you designed and implemented data models or ETL workflows that made a significant impact. This will demonstrate your analytical mindset and ability to translate business needs into technical solutions.
✨Collaboration is Key
Since this role involves working with AI engineers, data scientists, and business analysts, be ready to talk about your experience collaborating with cross-functional teams. Highlight any projects where you’ve successfully integrated solutions and how you communicated insights effectively to stakeholders.
✨Understand the Bigger Picture
Familiarise yourself with the company’s mission and how data engineering fits into their broader goals. Be prepared to discuss how your work can contribute to AI-driven business transformation and the importance of data quality and governance in achieving those objectives.
