National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Data Architect

Response Informatics
London
4 weeks ago
Applications closed

Related Jobs

View all jobs

Data Architect

Solution Architect, Data, AI, Microsoft Azure, Hands On, ETL, Remote

Enterprise Architect - Finance

Data Architect

Data Architect

Data Architect

Response Informatics is hiring for Data Architect


Role : Technical /Data Architect

Location : United kingdom


Responsibilities:

Data Architecture & Modeling:

  • Design end-to-end data architecture for loyalty platforms, ensuring seamless integration with CRMs, CDPs, DMPs, analytics platforms, and MarTech stacks.
  • Create logical and physical data models to support loyalty use cases—points accrual, redemption, tiering, customer preferences, and behavioral segmentation.
  • Define canonical data models and customer 360 views across systems and touchpoints.

Integration & Platform Enablement:

  • Collaborate with MarTech teams to ensure loyalty data flows smoothly into platforms like Salesforce, Adobe Experience Platform, Oracle CX, Braze, etc.
  • Define APIs, data pipelines, and ETL/ELT processes to ingest, transform, and activate data from multiple sources (web, mobile, POS, email, app).
  • Ensure architecture supports real-time data flows for triggers, personalization, and loyalty lifecycle messaging.

Data Governance & Quality:

  • Establish data governance policies, taxonomy standards, and metadata management practices for loyalty-related data.
  • Ensure data integrity, consistency, and compliance with privacy regulations (GDPR, CCPA, etc.).
  • Work closely with data stewards and engineers to enforce quality control and lineage tracking.
  • Partner with loyalty strategists, business analysts, and data scientists to align architecture with program objectives.

Collaboration & Strategy:

  • Support advanced analytics, ML models, and campaign optimization efforts with clean and structured datasets.
  • Evaluate and recommend technologies that enhance loyalty data capabilities (e.g., CDPs, identity resolution tools, consent management).

Qualifications:

  • 8+ years of experience in data architecture, data engineering, or enterprise data platforms, with a focus on marketing or customer data.
  • Strong understanding of loyalty program data structures and customer lifecycle management.
  • Proficient in data modeling, API architecture, cloud platforms (AWS, GCP, Azure), and relational/NoSQL databases.
  • Experience with MarTech integration and customer data platforms (CDPs) such as Adobe Experience Platform, Salesforce Data Cloud, or Segment.
  • Hands-on experience with tools like SQL, Python, Spark, Kafka, Airflow, or dbt.


Note : Sponsorship will be provided

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

LinkedIn Profile Checklist for Data Science Jobs: 10 Tweaks to Elevate Recruiter Engagement

Data science recruiters often sift through dozens of profiles to find candidates skilled in Python, machine learning, statistical modelling and data visualisation—sometimes before roles even open. A generic LinkedIn profile won’t suffice in this data-driven era. This step-by-step LinkedIn for data science jobs checklist outlines ten targeted tweaks to elevate recruiter engagement. Whether you’re an aspiring junior data scientist, a specialist in MLOps, or a seasoned analytics leader, these optimisations will sharpen your profile’s search relevance and demonstrate your analytical impact.

Part-Time Study Routes That Lead to Data Science Jobs: Evening Courses, Bootcamps & Online Masters

Data science sits at the intersection of statistics, programming and domain expertise—unearthing insights that drive business decisions, product innovation and research breakthroughs. In the UK, organisations from fintech and healthcare to retail and public sector are investing heavily in data-driven strategies, fuelling unprecedented demand for data scientists, machine learning engineers and analytics consultants. According to recent projections, data science roles will grow by over 40% in the next five years, offering lucrative salaries and varied career paths. Yet many professionals hesitate to leave their current jobs or pause personal commitments for full-time study. The good news? A vibrant ecosystem of part-time learning routes—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn data science while working. This comprehensive guide explores every pathway: foundational CPD units and short courses, hands-on bootcamps, accredited online MScs, plus funding options, planning strategies and a real-world case study. Whether you’re an analyst looking to formalise your skills, a software developer pivoting into data or a manager seeking to harness data-driven decision-making, you’ll find the right route to fit your schedule, budget and career goals.

The Ultimate Assessment-Centre Survival Guide for Data Science Jobs in the UK

Assessment centres for data science positions in the UK are designed to replicate the multifaceted challenges of real-world analytics teams. Employers combine psychometric assessments, coding tests, statistical reasoning exercises, group case studies and behavioural interviews to see how you interpret data, build models, communicate insights and collaborate under pressure. Whether you’re specialising in predictive modelling, NLP or computer vision, this guide provides a step-by-step roadmap to excel at every stage and secure your next data science role.