Posted Date
7/28/2025
Description
We are seeking a highly skilled and experienced Data Architect to join our team in order to deliver on major business priorities within the Client Financial Platform. As a Data Architect, you will play a critical role in designing, developing, and maintaining our data pipelines within and across our applications. You will lead a team of talented engineers, providing technical guidance and mentorship while ensuring the successful delivery of high-quality solutions. This role requires a deep understanding of data technologies, strong leadership skills, and a passion for data-driven decision-making.

QUALIFICATIONS:

• Data modeling: Expertise in various data modeling techniques, including relational, dimensional, and NoSQL.
• Data warehousing: Strong understanding of data warehousing concepts and experience with data warehouse design and implementation.
• ETL processes: Proficiency in designing and implementing Extract, Transform, Load (ETL) processes.
• Database management systems (DBMS): Extensive knowledge of various DBMS platforms, such as SQL Server, Oracle, and MySQL.
• Big data technologies: Familiarity with big data technologies like Hadoop, Spark, and NoSQL databases.
• Business Intelligence: Experience with various BI tools and technologies including Tableau, PowerBI, Microstrategy, etc.,
• Data governance: Understanding of data governance principles and best practices.
• Cloud computing: Experience with cloud-based data platforms like AWS, Azure, and GCP.
• Communication and collaboration: Excellent presentation, communication and interpersonal skills to effectively collaborate with stakeholders.

EXPERIENCE:

• 8+ years of experience

Education:

• Bachelors or Masters in Computer Science or equivalent field

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MOST RELEVANT SKILLS

Please see the requirements listed above.
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OTHER RELEVANT SKILLS

For complementary skills, please see above and/or contact the recruiter.
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• Design and implement data models: Develop conceptual, logical, and physical data models that meet business requirements.
• Develop data warehousing strategies: Design and implement data warehouses and data lakes to support business intelligence and analytics.
• Establish data governance policies: Define and enforce data quality standards, access controls, and security protocols.
• Collaborate with stakeholders: Work with data scientists, engineers, and business analysts to understand data needs and translate them into technical solutions.
• Evaluate and select data management tools: Research and recommend appropriate data management technologies and tools.
• Oversee data migration and integration: Manage the process of migrating data from legacy systems to new platforms.
• Performance tuning and optimization: Monitor and optimize data infrastructure performance to ensure efficient data access.
• Stay up-to-date with industry trends: Keep abreast of the latest developments in data management technologies and best practices.