Data Engineer - Data & Analytics Platforms

Senior Data Engineer - Data & Analytics Platforms

At IBM Consulting UK Future Now, you’ll build a career at the forefront of hybrid cloud and AI, working with leading clients across the public and private sectors. You’ll collaborate with top industry professionals, gain hands‑on experience with cutting‑edge technologies, and deliver solutions that create real business impact. From day one, you’ll work on meaningful, high‑profile programmes that stretch your skills and accelerate your growth.

• Work‑life balance
  : flexible working approaches, sabbatical programmes, paid paternity leave, maternity leave and an innovative maternity returners scheme.
• Traditional benefits
  : 25 days holiday (in addition to public holidays), private medical, dental & optical cover, online shopping discounts, an Employee Assistance Program, life assurance and a group pension plan through salary sacrifice.

In this role, you’ll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), delivering deep technical and industry expertise to public and private sector clients worldwide.

• Lead the design and development of robust data pipelines and data platforms to support analytics and AI workloads.
• Build and maintain batch and streaming data solutions, including ingestion, transformation, and orchestration.
• Design appropriate data models using relational, dimensional, or other modelling techniques.
• Collaborate across multiple teams and client stakeholders to design and deliver end‑to‑end data and AI solutions.
• Work across cloud‑based data platforms and services (e.g., AWS, Azure, or GCP).
• Design and deliver data solutions that are functionally correct and fit for purpose, while meeting non‑functional requirements such as security, performance, resilience and maintainability.
• Support and guide junior engineers through technical leadership and mentoring.
• Contribute to platform and engineering standards, best practices, and continuous improvement across engagements.

Required: None

Preferred: Bachelor’s Degree

• Strong experience with Python, SQL, and data engineering frameworks or tools.
• Proven experience designing and delivering data pipelines and data platforms in a professional environment.
• Hands‑on experience with cloud data services (e.g., Azure Data Factory, Databricks, Synapse, AWS Glue, Redshift, Big Query, or equivalents).
• Experience working with relational and/or No
  
  SQL databases.
• Solid understanding of data modelling, integration patterns, and data quality principles.
• Strong problem‑solving and communication skills, with experience working in multidisciplinary delivery teams.

• Familiarity with data pipeline orchestration tools (e.g., Apache Airflow, Luigi).
• Knowledge of data quality and metadata management practices.
• Understanding of data virtualisation and data federation techniques.
• Experience with big data technologies (e.g., Hadoop, Spark).
• Experience supporting analytics, data science, or machine learning use cases.
• Exposure to streaming or event‑driven architectures (e.g., Kafka or equivalent).
• Experience with CI/CD, infrastructure as code, or platform automation.
• Background delivering solutions in regulated or security‑constrained environments such as public sector or financial services.

This role is subject to pre‑employment screening in line with the UK Government’s Baseline Personnel Security Standard (BPSS). Additional personal security controls may apply.

IBM is proud to be an equal‑opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, disability, neurodivergence, age, or other characteristics protected by the applicable law. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

If you are interested in a flexible working pattern, please discuss with the recruitment team to find out if this is possible.