Data Architect

Data Architect - Corporate Engineering

Company Profile

LSEG (London Stock Exchange Group) is a world-leading financial markets infrastructure and data business. We are dedicated, open-access partners with a commitment to excellence in delivering services across Data & Analytics, Capital Markets, and Post Trade.

Backed by three hundred years of experience, innovative technologies, and a team of over 23,000 people in 70 countries, our purpose is driving financial stability, empowering economies, and enabling customers to create sustainable growth.

Role Profile
- In this role, you'll be joining our CRM, External Digital and Marketing team within Data and Integrations Team, Corporate Engineering (CE) as a Data Architect. This team works on data and integration requests by guiding customers on data migration cleansing, data quality techniques. This role impacts all divisional users of CRM Technology and downstream systems reliant on Customer Data - 7k users across Capital Markets, Post Trade and Data & Analytics.

The data and integrations team do this by:

- Conducting data quality analysis, end to end data reconciliations by profiling the source systems using ETL /SQL (IICS /Matillion/AWS Glue).
- Building Enterprise Data Architecture or Data Lake for the Migration projects
- Defining the data quality of the sources and lists the data quality metrics of the source systems.
- Working on detailed scoping and requirements working with business customers, SMEs, Technology Partner organizations and internal CRM Technology and Corporate Technology teams.
- Building and maintaining Customer Master and Product Master.
- Continuously review operating metrics and data to find opportunities to improve.

Tech Profile/Essential Skills
- 12 years of technical experience.
- 7 years of experience on data migration and reporting using ETL and Reporting Tools
- 5 years of experience on ETL/Database Development
- 2 years of experience on Salesforce Data Migration projects
- Expert level skill on Informatica IICS or Matillion or AWS Glue or equivalent ETL tool which covers from extracting the source to building the complex mappings.
- Proficient in the use or extract of data from Salesforce.
- Must have knowledge on the Salesforce Data modelling.
- Must have Experience on Snowflake Storage and Database.
- Expert level coding knowledge on Python to do ETL.
- Able to translate business requirements into data solutions.
- Understanding of Salesforce concepts.
- Snowflake development.
- Experience with providing technical solutions and supporting documentation.

Preferred Skills and Experience
- Experience of Tableau and/or Power BI reporting preferred for management reporting.
- Understanding of the SDLC and agile delivery methodology.
- Should have experience with Enterprise Architect or Erwin Data modeler
- Ability to handle own work and multitask to meet tight deadlines without losing sight of priorities under minimum supervision.
- Highly motivated, self-directed individual with a positive & pro-active demeanor to work.
- Customer and service focused, with determination to meet their needs and expectations.
- Be driven and committed to the goals and objectives of the team and organization.

Education and Professional Skills
- Professional qualification or equivalent.
- BS/MS degree in Computer Science, Software Engineering or STEM degree (Desirable).
- Curious about new technologies and tools, creative thinking and initiative taking.
- Agile related certifications preferable.

Detailed Responsibilities
- Proficient in data discovery, data migration, data quality analysis, end to end data reconciliations by profiling the source systems using ETL /SQL (IICS /Matillion Preferable).
- Analyses the data quality of the sources and lists the data quality metrics of the source systems.
- Domain expert in MDM and Customer data.
- Lead the Single Customer View and Customer 360 implementations.
- Lead the data migration strategies for large scale programs.
- Data mining to uncover patterns, anomalies, and correlations in large data sets.
- Data management to efficiently and cost-effectively collect, store, and use data.
- Machine learning to build scalable systems for handling Big Data Systems.
- Structured query language (SQL) to manipulate data.
- Data modelling tools like Erwin or Visio to visualize metadata and database schema.
- Creating and implementing data management processes and procedures
- Researching data acquisition opportunities.
- Develops and improves data governance and business data processes within the Technology and business organizations and understands client requirements, specifying and analyzing these to a sufficient level of detail to ensure transparency of definition and ability for technical teams to translate to a technical solution design.
- Works with developers, architects, and solution designers to translate sophisticated business requirements and provides feedback on technical solutions proposed.
- Res