Senior Data Architect

Job Description

Principal – Cloud Data Architect | London Stock Exchange Group

The Tone:
This is a manager-level role at London Stock Exchange Group, operating globally with headquarters in the United Kingdom. LSEG’s Risk Intelligence division provides critical insights and solutions, leveraging advanced analytics to help clients manage risk and navigate global commerce complexities. As a Senior Data Architect within the Digital Identity & Fraud Engineering team, this role is crucial for setting technical direction, ensuring the use of appropriate technologies, and driving customer value and operational efficiency in the global financial fraud landscape. It involves significant leadership and mentorship, ensuring the team’s capabilities align with product delivery needs.

The TL;DR
• Role: Manager
• Location: Global (UK Headquartered)
• Team: Digital Identity & Fraud Engineering team
• Mission: To provide technical direction for products, ensuring appropriate technology usage, driving customer value, and operational efficiency within the Digital Identity & Fraud Engineering team.
• Tech Stack: AWS, Azure, GCP, Kafka, Kinesis, DataFlow, Airflow, MongoDB, DynamoDB, HBase, CosmosDB, GraphQL, Snowflake, DataBricks, SQL, Python

What You’ll Actually Do
• [Architecture Design]: Design secure, scalable, and cost-effective data architectures for various solutions.
• [Technology Leadership]: Lead the adoption and integration of AWS/Azure architecture services across multi-functional teams.
• [Strategic Planning]: Interpret and deliver strategic plans to enhance data integration, quality, and delivery for business initiatives and roadmaps.
• [Solution Optimization]: Formulate and articulate architectural trade-offs across solution options before recommending an optimal solution.
• [Technical Mentorship]: Motivate and develop staff through teaching, empowering, and influencing technical skills.

The Must-Haves
• Background: Manager-level professional with expertise in digital identity, fraud engineering, and the global financial fraud landscape.
• Experience: 12+ years implementing on-premises and cloud data management, integration, visualization, and analytical technologies; advanced proficiency in end-to-end data architecture solutions including ingestion, storage, and relational modeling; demonstrated proficiency in designing and implementing modern data architectures and concepts.
• Skills: SQL, Python, AWS, Azure, GCP, real-time data distribution (e.g., Kafka, Kinesis, DataFlow, Airflow), NoSQL databases (e.g., MongoDB, DynamoDB, HBase, CosmosDB), GraphQL, modern data warehouse tools (Snowflake, DataBricks), strategic thinking, and the ability to assess traditional and modern data architectural components based on business needs.
• Bonus: Familiarity with recommending data governance best practices including MDM, security, privacy, and policies.