Data Engineer

Job Description

hackajob is collaborating with Accenture to connect them with exceptional professionals for this role.

\n

Role: Data Engineer
Location: Newcastle Upon Tyne
Salary: TBC – Depending on experience
Levels: Senior Analyst, Specialist

\n

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

\n

\n

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.

\n

Note: The above information relates to a specific client requirement

\n

\n

About the Team

\n

\n

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.

\n

\n

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.

\n

Role Overview

\n

\n

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.

\n

\n

Key Responsibilities

\n

\n

Data Pipeline Development

\n

\n
• \nBuild, optimize, and maintain scalable data pipelines using Java (primary), plus exposure to Python, Flink, Kafka, or Spark.\n

\n

• \nDevelop and support real‐time streaming pipelines and event‐driven integrations.\n

\n

• \nIntegrate data from multiple sources (streaming, batch, APIs) using AWS managed services (e.g., Kinesis, MSK, Lambda, Glue).\n

\n\n

Data Architecture & Standards

\n

\n
• \nContribute to data modelling, data architecture best practices, and modern patterns (e.g., medallion architecture).\n

\n

• \nEnsure data quality, lineage, governance, and security controls are applied consistently.\n

\n\n

DevOps & Deployment

\n

\n
• \nDeploy and maintain data applications using CI/CD tooling (Azure DevOps, GitHub Actions, Jenkins).\n

\n

• \nUse Infrastructure as Code (e.g., Terraform, CloudFormation) to manage cloud environments.\n

\n

• \nWork with container technologies such as Docker and Kubernetes‐based workloads.\n

\n\n

\n

Collaboration

\n

\n
• \nWork closely with analytics, ML/AI, and product teams to deliver clean, well‐structured datasets.\n

\n

• \nParticipate in code reviews and internal knowledge‐sharing sessions.\n

\n

• \nProvide guidance to junior engineers where needed.\n

\n\n

Qualification
\n

\n

Core Data Engineering

\n

\n
• \nStrong programming proficiency in Java (preferred) or Python.\n

\n

• \nHands-on experience with at least one of: Kafka, Flink, Spark (Flink/Kafka preferred for streaming).\n

\n

• \nSolid understanding of stream processing concepts (e.g., event time, state, backpressure).\n

\n

• \nUnderstanding of software engineering best practices: testing, design patterns, CI/CD, Git.\n

\n

• \nExperience building ETL/ELT or streaming data pipelines.\n

\n

• \nExposure to microservices and distributed system concepts.\n

\n

• \nExperience working with cloud platforms, ideally AWS, but Azure/GCP also acceptable.\n

\n

• \nUnderstanding of distributed compute, large-scale data systems, and performance considerations.\n

\n\n

\n

DevOps & Engineering Practices

\n

\n
• \nExperience with CI/CD tools (Azure DevOps, GitHub Actions, Jenkins etc.).\n

\n

• \nInfrastructure‐as‐Code (Terraform preferred).\n

\n

• \nExperience with containerisation (Docker) and orchestration platforms (Kubernetes/EKS).\n

\n\n

\n

Certifications & Tools

\n

\n
• \nExposure to enterprise data platforms (Databricks, Snowflake, BigQuery, or similar).\n

\n

• \nCloud certifications (AWS, Azure, GCP) are beneficial but not required.\n

\n\n

\n

Other Requirements

\n

\n

\n
• \nMinimum 3 years’ experience working on data engineering or large-scale data solutions.\n

\n

• \nComfortable working in Agile delivery teams.\n

\n

• \nStrong communication skills and ability to collaborate with technical and non‐technical stakeholders.\n

\n\n

\n

Desirable

\n

\n
• \nExperience in client-facing or consulting environments.\n

\n

• \nProfessional cloud or data engineering certifications.\n

\n

• \nExperience mentoring or supporting junior engineers.\n

\n

• \nBackground in designing or operating real‐time, low-latency systems.\n

\n\n

About Accenture
\n

\n

We work with one shared purpose: to deliver on the promise of technology and human ingenuity. Every day, more than 775,000 of us help our stakeholders continuously reinvent. Together, we drive positive change and deliver value to our clients, partners, shareholders, communities, and each other.

\n

We believe that delivering value requires innovation, and innovation thrives in an inclusive and diverse environment. We actively foster a workplace free from bias, where everyone feels a sense of belonging and is respected and empowered to do their best work.

\n

At Accenture, we see well-being holistically, supporting our people’s physical, mental, and financial health. We also provide opportunities to keep skills relevant through certifications, learning, and diverse work experiences. We’re proud to be consistently recognized as one of the World’s Best WorkplacesTM.