Description
Risk Intelligence is a key division within LSEG, dedicated to providing critical insights and solutions that help clients manage and mitigate risk.
We're looking for a Senior Data Architect to work in the Digital Identity & Fraud Engineering team. As a Senior Technologist, you'll be responsible for the technical direction of our Products, ensuring that we are using appropriate technologies and helping drive initiatives to bring customer value and efficiency in operation.
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
- Interpreting and delivering impactful strategic plans improving data integration, data quality, and data delivery
- Formulating and articulating architectural trade-offs across solution options
- 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
- 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 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