Senior Consultant & Data Engineer AI & Data

Ernst & Young Advisory Services Sdn Bhd; City Of London; On-site; GBP 60,000 - 80,000; Full time

Job summary

A global consulting firm is seeking a Data Engineer Senior Consultant to design and optimize data solutions in London. The ideal candidate will have a degree in Computer Science and experience with modern data engineering practices. You will work on developing data pipelines for various business domains, focusing on quality and efficiency. Strong skills in Python and SQL are essential. The position offers the opportunity to work in a collaborative environment that values innovation and transformation.

Qualifications

• Degree or equivalent certification in Computer Science, Data Engineering, or related field.
• Proven experience in building and maintaining large-scale data pipelines.
• Strong programming skills in Python and SQL.

Responsibilities

• Design, develop, and deploy end-to-end data pipelines for complex business problems.
• Collaborate with AI engineers and data scientists to deliver integrated solutions.
• Ensure data quality, integrity, and governance throughout the data lifecycle.

Skills

Data pipeline development

Python programming

SQL proficiency

Data modeling

Data governance

Analytical skills

Team collaboration

Education

Degree in Computer Science or related field

Tools

Databricks

Azure Data Factory

Snowflake

Airflow

Job description

Senior Consultant, Data Engineer, AI&Data, UKI, London

Location: London

Other locations: Primary Location Only

Requisition ID: 1654633

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Data Engineer Senior Consultant – Job Specification

Location: London

Position Overview

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.
• 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:
• AWS Certified Data Analytics – Specialty
• SnowPro Advanced: Data Engineer

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