Data Engineer (AI and Automation)

Talantir; Milton Keynes; Hybrid; GBP 45,000 - 55,000; Full time

Job summary

Talantir in Milton Keynes is recruiting a Data Engineer (AI and Automation) to design, build, and optimise automated data pipelines across Azure and on-prem environments. Hybrid work with 3 days in-office weekly, focusing on scalable analytics and AI-ready data.

The role requires hands-on experience delivering end-to-end data solutions, with exposure to AI-enabled workflows and data governance. You will collaborate with global teams, solution architects, and data stakeholders to advance the

Qualifications

• Proven experience delivering automated end-to-end data engineering solutions.
• Advanced SQL skills with performance tuning on large datasets.
• Python or R for data processing and analytics.
• Hands-on with cloud and on-prem data integration tools like Azure Data Factory and Databricks.
• Strong data modelling, warehousing, and relational database experience.

Responsibilities

• Design and maintain fully automated end-to-end data pipelines.
• Ensure secure, reliable data ingestion, transformation, and delivery.
• Implement AI-enabled automation and optimisation opportunities.
• Prepare AI-ready data models and datasets for analytics and ML use cases.
• Monitor and optimise data operations, with incident management and governance considerations.
• Contribute to CI/CD, orchestration, and platform enhancements for scalable data foundations.

Skills

Advanced SQL

Python

Azure Data Factory

Databricks

Data modelling

Data warehousing

Data integration

Agile / DevOps

Tools

Azure Data Factory

Databricks

MS SQL Server

Job description

Role: Data Engineer (AI and Automation) Location: Milton Keynes (Hybrid – 3 Days In-Office Weekly) Salary: £45,000 – £55,000 Network IT are partnering with a large, enterprise‑scale organisation undergoing significant modernisation of their data and automation platforms. We’re seeking an experienced Data Automation Engineer to design, build, and optimise secure, highly automated data pipelines that enable scalable analytics, AI‑ready data, and intelligent, data‑driven operations across the business. This role is suited to someone with hands‑on experience delivering robust end‑to‑end data solutions, strong automation capability, and growing exposure to AI‑enabled data workflows, including opportunities to influence how LLMs and AI automation are embedded into the organisation’s data estate.

Role Overview and Responsibilities

As a Data Automation Engineer, you will take ownership of the delivery, operation, and continuous improvement of automated data pipelines and platform components across Azure and on‑prem environments. You’ll work closely with Data Engineers, Solution Architects, Application Managers, and international teams to ensure data operations are scalable, resilient, and aligned with governance and quality standards.

Key responsibilities include:

• Designing, building, and maintaining fully automated end‑to‑end data pipelines, ensuring secure, reliable data ingestion, transformation, delivery, and documentation.
• Delivering high‑quality data flows using tools such as Azure Data Factory, Databricks, SQL, and Python, reducing manual intervention through standardisation and automation.
• Identifying and implementing improvements in speed, reliability, and scalability, including opportunities to apply AI‑supported automation and optimisation.
• Preparing and maintaining high‑quality datasets and AI‑ready data models (DWH / Lakehouse) to support analytics, reporting, and machine‑learning use cases.
• Monitoring and troubleshooting daily data operations, resolving issues following ITIL best practices, and implementing proactive improvements, alerting, and self‑healing mechanisms.
• Enhancing pipeline performance and observability, improving monitoring, alerting, and automated preventative rules.
• Supporting data governance processes such as data quality, lineage, masking, encryption, archiving, and compliance, with increasing automation maturity.
• Contributing to CI/CD processes, orchestration, scheduling, and platform‑level enhancements to support scalable, AI‑enabled data foundations.
• Collaborating with cross‑functional and international teams to align changes, share best practices, and support the execution of the organisation’s data strategy.

Essential Skills and Experience

To be successful in this role, you will bring:

• Proven experience delivering automated end‑to‑end data engineering solutions in complex environments.
• Advanced SQL skills, including performance tuning and optimised queries across large datasets to prepare AI‑ready data.
• Knowledge of Python (or R) for data processing, transformation, or analytics.
• Hands‑on experience with cloud and on‑prem data integration tools such as Azure Data Factory and Databricks.
• Strong background in data modelling, data warehousing, and relational database environments (e.g., MS SQL Server).
• Experience designing cloud‑native and on‑prem data solutions.
• Exposure to AI/ML initiatives, AI‑enabled automation, and an understanding of LLM concepts and their data workflow applications.
• Experience working in Agile environments (Scrum, Kanban, DevOps).
• Strong analytical, problem‑solving, and communication skills, with the ability to work effectively across technical and non‑technical teams.