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Blue Acorn iCi

Data Architect / Data Engineer (EMEA)

Reposted 15 Days Ago
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Remote
Hiring Remotely in United Kingdom
Mid level
Remote
Hiring Remotely in United Kingdom
Mid level
The Data Architect/Data Engineer will design scalable data architectures, build and optimize data pipelines, ensure data governance, and support advanced analytics and personalization, particularly using Adobe Experience Platform.
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  ​ Blue Acorn iCi is Expanding Across Europe!
We’re growing — and we’re looking for top digital talent across the UK!

📍 Location & Eligibility

This role is based in the UK (London area) and follows a hybrid working model. We’re ideally looking for candidates who are already located nearby or open to commuting as needed.
Please note that applicants must have the current right to work in the UK, as we’re not able to offer visa sponsorship for this position at this time.

Data Architect / Data Engineer

About the Role

We’re looking for a Data Architect / Data Engineer to design and power the data foundation behind large-scale, data-driven customer experiences.

In this role, you’ll be responsible for building and optimizing the data architecture that fuels real-time segmentation, personalization, and analytics, with Adobe Experience Platform (AEP) at the core.

You’ll work across marketing, analytics, and engineering teams to ensure data is clean, connected, and activation-ready—enabling everything from campaign execution to AI-driven personalization.

This is a hands-on role for someone who enjoys solving complex data challenges and building scalable, high-performance data ecosystems.

What You’ll Do

Design Data Architecture

  • Design and implement scalable data architectures supporting real-time data ingestion and activation
  • Define data models, schemas, metadata, and identity frameworks
  • Ensure architecture supports segmentation, personalization, and analytics use cases

Build & Integrate Data Pipelines

  • Develop and maintain integrations between Adobe Experience Platform (AEP) and enterprise systems
  • Build and optimize data pipelines (ETL/ELT) across multiple data sources
  • Ensure reliable connectivity across marketing, analytics, and product platforms

Optimize Data Infrastructure

  • Improve performance and reliability of data pipelines and ingestion processes
  • Support both batch and real-time data processing requirements
  • Monitor system performance and resolve bottlenecks or failures

Ensure Data Governance & Compliance

  • Implement data governance frameworks including ownership, metadata, and schema standards
  • Ensure compliance with GDPR and global data privacy regulations
  • Support data lifecycle management, retention, and data quality initiatives

Enable Advanced Analytics & Personalisation

  • Support data science and analytics teams with high-quality, structured data
  • Enable AI-driven segmentation and personalization use cases
  • Provide the foundation for advanced analytics and performance measurement

What Success Looks Like

  • Scalable, high-performing data architecture supporting global digital experiences
  • Reliable, real-time data pipelines with minimal latency or downtime
  • Clean, well-governed data ready for activation and analytics
  • Strong alignment between data, marketing, and product teams
  • A future-ready platform supporting AI and advanced personalization

What We’re Looking For

  • Strong experience in data architecture, data engineering, or data platform development
  • Hands-on experience building data pipelines, integrations, and data models
  • Experience with Adobe Experience Platform (AEP) or similar CDP/data platforms
  • Strong understanding of real-time data processing, APIs, and cloud-based architectures
  • Experience supporting marketing and analytics use cases with data solutions
  • Knowledge of data governance, privacy, and compliance frameworks (GDPR)
  • Ability to work cross-functionally in fast-paced, large-scale environments

Nice to have:

  • Experience supporting personalization or customer engagement platforms
  • Exposure to AI/ML-driven data use cases
  • Background in high-scale consumer or digital platforms

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