At a Glance
- Tasks: Design and govern data architectures for business intelligence and AI initiatives.
- Company: Join a forward-thinking company shaping the future of data and analytics.
- Benefits: Attractive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborate with top tech leaders and work on cutting-edge technologies.
- Why this job: Be at the forefront of data engineering and influence strategic technology decisions.
- Qualifications: 15+ years in Data Engineering with strong leadership and technical skills.
The predicted salary is between 80000 - 100000 £ per year.
About the Role
As a Data Engineering Architect, you will be responsible for designing and governing end-to-end data architectures that support business intelligence, advanced analytics, machine learning, and AI initiatives. You will work closely with business leaders, data scientists, architects, and engineering teams to build scalable data solutions that transform raw data into actionable insights.
Responsibilities
- Define and implement enterprise-wide data architecture and engineering strategies
- Design scalable, secure, and high-performance data platforms across cloud and hybrid environments
- Build modern data ecosystems that support analytics, reporting, AI, and machine learning workloads
- Design, develop, and optimize batch and real-time data pipelines
- Build robust ETL/ELT frameworks for data ingestion, transformation, and processing
- Integrate structured, semi-structured, and unstructured data from multiple enterprise sources
- Architect scalable data lake, data warehouse, and lakehouse solutions
- Ensure data reliability, quality, governance, and security across platforms
Cloud & Big Data Solutions
- Lead cloud-native data platform implementations across AWS, Azure, and GCP
- Design architectures supporting real-time analytics and event-driven data processing
- Source technologies: Spark, Hadoop, Kafka, Kinesis, Streaming Technologies
AI & Advanced Data Enablement
- Build AI-ready data foundations supporting predictive analytics and machine learning initiatives
- Work with Graph Databases and Vector Databases to enable next-generation AI and knowledge-driven applications
- Collaborate with Data Science and AI teams to accelerate enterprise AI adoption
Leadership & Governance
- Drive best practices in Data Engineering, Data Governance, Security, and DevOps
- Lead architecture reviews, technology evaluations, and strategic initiatives
- Mentor engineering teams and influence enterprise data standards
- Partner with stakeholders to translate business requirements into scalable technical solutions
What We're Looking For
Core Experience
- 15+ years of experience in Data Engineering, Data Architecture, or Enterprise Data Management
- Proven track record of designing and implementing large-scale enterprise data platforms
- Strong leadership, stakeholder management, and solution architecture experience
Technical Expertise
- Programming: Python, Java, Spark, ETL/ELT Frameworks, Data Lakes, Data Warehouses
- Databases: SQL & NoSQL, Redshift, DynamoDB, MongoDB, Synapse, BigQuery, RDS, AWS, GCP, Hadoop, Kafka, Kinesis
- Data Warehousing: Snowflake, Redshift, BigQuery
- DevOps & Automation: CI/CD, Docker, Infrastructure Automation
- APIs & Integration: REST APIs, Messaging Platforms
- Graph Databases: Amazon Neptune, RDF4J, Neo4j
- Vector Databases: Pinecone, FAISS
- Experience with Informatica, Talend, dbt
- Exposure to NLP Solutions, AI/ML Platforms, Customer Segmentation & Advanced Analytics, Banking, Insurance, Mortgage
Shape the Future of Cloud, Analytics, and AI Architecture. Work on cutting-edge technologies including Big Data, Real-Time Analytics, Graph Databases, and AI-ready platforms. Collaborate with senior technology leaders and business stakeholders. Influence strategic technology decisions across the organization. Build platforms that power data-driven innovation at scale. Ready to architect the future of enterprise data? If you're passionate about Data Engineering, Cloud Architecture, Big Data, Analytics, and AI-driven innovation, we'd love to connect with you.
Data Engineering Architect in London employer: Mphasis
As a leading employer in the tech industry, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to excel. Our Data Engineering Architects enjoy competitive benefits, continuous professional development opportunities, and the chance to work with cutting-edge technologies in a dynamic environment. Located in a vibrant area, we offer a unique blend of career growth and work-life balance, making us an attractive choice for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineering Architect in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field and let them know you're on the lookout for opportunities. Attend industry meetups or webinars to meet potential employers and showcase your expertise.
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your best projects, especially those involving data architecture and machine learning. This will give you an edge when chatting with hiring managers and help them see what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process when designing scalable data solutions, as this will demonstrate your problem-solving abilities to potential employers.
✨Tip Number 4
Don't forget to apply through our website! We have a range of exciting roles that could be perfect for you. Plus, applying directly shows your enthusiasm and commitment to joining our team at StudySmarter.
We think you need these skills to ace Data Engineering Architect in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Data Engineering Architect role. Highlight your experience in designing data architectures and working with cloud platforms, as this will catch our eye!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your background makes you a perfect fit for our team. Don’t forget to mention any relevant projects or achievements.
Showcase Your Technical Skills:We love seeing technical expertise! Be sure to list your programming languages, tools, and technologies you’ve worked with, especially those mentioned in the job description like Python, Spark, and AWS. This helps us see your fit right away.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows us you’re serious about joining StudySmarter!
How to prepare for a job interview at Mphasis
✨Know Your Data Architecture Inside Out
Make sure you’re well-versed in the latest data architecture trends and technologies. Brush up on your knowledge of cloud platforms like AWS, Azure, and GCP, as well as tools like Spark and Kafka. Being able to discuss how you've implemented these in past projects will show your expertise.
✨Showcase Your Leadership Skills
As a Data Engineering Architect, you'll need to lead teams and influence stakeholders. Prepare examples of how you've successfully managed projects or mentored others in your previous roles. This will demonstrate your ability to drive best practices and governance in data engineering.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions during your interview. Be ready to explain your experience with ETL/ELT frameworks, data lakes, and real-time analytics. Practising coding problems or system design scenarios can help you articulate your thought process clearly.
✨Align with Business Goals
Understand how data architecture supports business intelligence and AI initiatives. Be prepared to discuss how your designs can transform raw data into actionable insights that align with the company's strategic goals. This shows that you’re not just a techie but also a business-minded professional.
