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Job Description
Seeking a Data Architect to define and implement data architecture and governance for a cutting-edge platform leveraging AI to address complex challenges in the financial industry.
Our Limerick-based client is a thriving company with excellent career development opportunities. The successful candidate will play a critical role in building and maintaining the company's platform, ensuring data integrity, security, and accessibility while collaborating with development teams, product managers, and stakeholders.
The platform will leverage the power of artificial intelligence to address the complex challenges of fraud detection, risk assessment, and regulatory compliance in the financial industry.
Key Responsibilities:
- Provide technical leadership to establish data architecture standards, principles, and best practices in collaboration with cross-functional teams, including data science and product departments.
- Lead conversations and workshops with stakeholders to understand requirements and identify solutions and opportunities.
- Define data structures, mappings, and flows to enable performance data processing and analysis.
- Establish and implement data strategy and governance process, ensuring data quality, consistency, accessibility, and compliance with regulatory requirements.
- Research and evaluate data technologies and tools to support business goals, including hands-on technical evaluation and PoCs.
- Design and implement ETL (Extract, Transform, and Load) flows in a cloud-native environment.
- Design and implement data storage solutions, including caching, partitioning, and indexing to improve performance.
- Produce and contribute to high-quality documentation.
Key Requirements:
- Bachelor's degree in a relevant discipline.
- 5+ years of experience in data architecture, modeling, and data management solutions.
- Experience working in the financial services, financial technology, and risk management industry.
- Excellent problem-solving and decision-making skills.
- Excellent interpersonal and communication skills, comfortable presenting technical information to a non-technical audience.
- In-depth knowledge of relational databases (e.g., Postgre SQL, My SQL) and familiarity with No SQL databases (e.g., Mongo DB, Dynamo DB, Neo4 J, etc.).
- Knowledge of data storage and analytics solutions (e.g., Snowflake, Data Bricks).
- Knowledge of data visualization tools (e.g., Tableau, Looker, Sigma, Power BI).
- Experience designing cloud-based data platforms and streaming flows (e.g., AWS, GCP, Azure).
- Experience with AI and MLOps architecture approaches, ensuring seamless integration and performance.
- Experience with streaming data platforms (e.g., Kafka, Kinesis).
- Familiarity with Vector and Graph database architecture.