Principal - Cloud Data Architect
Why Join Us?
Global Impact: Headquartered in the United Kingdom, we operate in 70 countries across EMEA, North America, Latin America, and Asia Pacific.
Diverse Workforce: We employ 25,000 people globally, with more than half located in Asia Pacific.
Legacy of Excellence: Our ticker symbol, LSEG, represents our long-standing commitment to financial markets. Join us and be part of a team that is driving innovation and making a difference!
About the Role
We're looking for an exceedingly versatile Senior Data Architect to work in Digital Identity & Fraud Engineering team.
Responsibilities
Designing secure, scalable, and cost-effective data architecture.
Working with multi-functional teams to lead the adoption and integration of AWS/Azure architecture services.
Collaborating with data engineers to prepare and deliver raw data for prescriptive and predictive modeling.
Assessing and advocating data management technologies and practices.
Eliminating gaps between the current state and a well-targeted future state.
Interpreting and delivering impactful strategic plans.
Improving data integration, data quality, and data delivery in support of business initiatives and roadmaps.
Formulating and articulating architectural trade-offs across solution options before recommending an optimal solution.
Motivating and developing staff through teaching, empowering, and influencing technical skills.
Collaborating with customers and development staff to ensure data architecture recommendations improve the value of client data across the organization.
Driving innovative technology solutions through thought leadership on emerging trends.
Sharing project solutions and outcomes with colleagues to improve delivery on future projects.
Skills/Experience
12+ years of proven ability implementing with a variety of 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 using industry standard languages including SQL and Python.
Demonstrated proficiency in the design and implementation of modern data architectures and concepts such as cloud services (e.g., AWS, Azure, GCP), real-time data distribution (e.g., Kafka, Kinesis, DataFlow, Airflow), NoSQL (e.g., MongoDB, DynamoDB, HBase, CosmosDB), GraphQL, and modern data warehouse tools including Snowflake and DataBricks.
Ability to think strategically and relate architectural decisions and recommendations to customer needs.
Ability to assess traditional and modern data architectural components based on business needs.
Familiarity with recommending data governance standard methodologies including MDM, security, privacy, and policies.