Data Engineer - Newcastle

Accenture UK & Ireland; Newcastle upon Tyne; Hybrid; GBP 65.000 - 90.000; Vollzeit

Zusammenfassung

Accenture UK & Ireland is seeking a Data Engineer in Newcastle upon Tyne to design, build, and maintain scalable data pipelines enabling analytics, AI, and operational insights. You will work with client and internal teams to deliver robust data solutions in a hybrid setup.

The role requires 3+ years in data engineering, strong Java/Python skills, and experience with Kafka, Spark, and cloud platforms (AWS preferred).

Qualifikationen

• Minimum 3 years' experience in data engineering or large-scale data solutions.
• Experience with data pipelines, streaming data, and cloud architectures.
• Strong communication and collaboration skills.

Aufgaben

• Design, build, and maintain scalable data pipelines for analytics and AI.
• Develop real-time streaming pipelines and event-driven integrations.
• Collaborate with analytics ML/AI and product teams to deliver data assets.

Kenntnisse

Java

Python

Kafka

Spark

AWS

CI/CD

Kubernetes

Ausbildung

Bachelor's degree in Computer Science or related field

Tools

Docker

Terraform

Azure DevOps

Git

Jenkins

Jobbeschreibung

Data Engineer

Role: Data Engineer

Location: Newcastle Upon Tyne

Salary: TBC – Depending on experience

Levels: Senior Analyst, Specialist

Hybrid Working: 3 days per week in our Newcastle, Cobalt business park office

Please Note: Any offer of employment is subject to satisfactory BPSS and SC security clearance which requires 5 years continuous UK address history (typically including no periods of 30 consecutive days or more spent outside of the UK) and declaration of being a British or EU passport holder or hold Indefinite Leave to remain within the UK at the point of application.

Note: The above information relates to a specific client requirement

About The Team

Our Advanced Technology Centre is a hub of innovation where we deliver high‑quality data and technology services to clients across both the public and private sectors. You’ll join a collaborative culture that values diverse thinking, continuous learning, and opportunities for career growth within a global network of experts.

If you're looking for a dynamic role that offers hands‑on experience with modern data technologies and the chance to shape large‑scale data solutions, this position offers you the opportunity to develop and progress rapidly.

Role Overview

As a Data Engineer, you will design, build, and maintain scalable data solutions that enable analytics, AI, and operational insights. You’ll work alongside client and internal teams to create robust data pipelines, ensure data reliability, and support cloud‑based architectures that power intelligent decision‑making.

Key Responsibilities

Data Pipeline Development

• Build, optimize, and maintain scalable data pipelines using Java (primary), plus exposure to Python, Flink, Kafka, or Spark.
• Develop and support real‑time streaming pipelines and event‑driven integrations.
• Integrate data from multiple sources (streaming, batch, APIs) using AWS managed services (e.g., Kinesis, MSK, Lambda, Glue).

Data Architecture & Standards

• Contribute to data modelling, data architecture best practices, and modern patterns (e.g., medallion architecture).
• Ensure data quality, lineage, governance, and security controls are applied consistently.

DevOps & Deployment

• Deploy and maintain data applications using CI/CD tooling (Azure DevOps, GitHub Actions, Jenkins).
• Use Infrastructure as Code (e.g., Terraform, CloudFormation) to manage cloud environments.
• Work with container technologies such as Docker and Kubernetes‑based workloads.

Collaboration

• Work closely with analytics, ML/AI, and product teams to deliver clean, well‑structured datasets.
• Participate in code reviews and internal knowledge‑sharing sessions.
• Provide guidance to junior engineers where needed.

Core Data Engineering

• Strong programming proficiency in Java (preferred) or Python.
• Hands‑on experience with at least one of: Kafka, Flink, Spark (Flink/Kafka preferred for streaming).
• Solid understanding of stream processing concepts (e.g., event time, state, backpressure).
• Understanding of software engineering best practices: testing, design patterns, CI/CD, Git.
• Experience building ETL/ELT or streaming data pipelines.
• Exposure to microservices and distributed system concepts.
• Experience working with cloud platforms, ideally AWS, but Azure/GCP also acceptable.
• Understanding of distributed compute, large‑scale data systems, and performance considerations.

DevOps & Engineering Practices

• Experience with CI/CD tools (Azure DevOps, GitHub Actions, Jenkins etc.).
• Infrastructure‑as‑Code (Terraform preferred).
• Experience with containerisation (Docker) and orchestration platforms (Kubernetes/EKS).

Certifications & Tools

• Exposure to enterprise data platforms (Databricks, Snowflake, BigQuery, or similar).
• Cloud certifications (AWS, Azure, GCP) are beneficial but not required.

Other Requirements

• Minimum 3 years’ experience working on data engineering or large‑scale data solutions.
• Comfortable working in Agile delivery teams.
• Strong communication skills and ability to collaborate with technical and non‑technical stakeholders.

Desirable

• Experience in client‑facing or consulting environments.
• Professional cloud or data engineering certifications.
• Experience mentoring or supporting junior engineers.
• Background in designing or operating real‑time, low‑latency systems.