Kafka Developer
Apply NowCompany: Diamondpick
Location: Toronto, ON M4E 3Y1
Description:
Role: ETL Data Modeler
Location : Toronto, ON (Hybrid)
Key Responsibilities:
Qualifications:
Location : Toronto, ON (Hybrid)
Key Responsibilities:
- Design and develop sophisticated data models for trade data related to various financial instruments, ensuring alignment with business needs and regulatory requirements.
- Work closely with the Director, Data and Architecture Services, Trade Data, to understand strategic objectives and contribute to the overall data architecture strategy.
- Collaborate with business analysts, data engineers, and IT teams to gather requirements and translate business needs into technical specifications.
- Create and maintain logical and physical data models, ensuring optimal performance and compliance with internal and external standards.
- Ensure data models are flexible and scalable to support the introduction of new products and adapt to changes in market practices.
- Manage metadata repositories and data dictionaries, promoting data quality and consistency across the organization.
- Review data models with stakeholders, validating design decisions and ensuring data integrity.
- Advise on data normalization, storage solutions, and efficient data retrieval methods.
- Participate in data governance initiatives, supporting the development and enforcement of data policies and standards.
- Stay abreast of industry trends, tools, and regulatory changes that impact data modeling and capital markets.
Qualifications:
- Bachelor's or Master's degree in Computer Science, Information Systems, Finance, or a related field.
- Minimum of 5 years of experience in data modeling, with a strong preference for candidates with capital markets experience.
- Expert knowledge of financial products, trade lifecycle, and market data.
- Proficiency in data modeling tools (e.g., ERwin, PowerDesigner, IBM Data Architect) and familiarity with database technologies (SQL, NoSQL).
- Experience with data warehousing, ETL processes, and big data platforms.
- Excellent analytical, problem-solving, and organizational skills.
- Effective communication skills, with the ability to interact with a variety of stakeholders.
- Understanding of financial regulations (e.g., GDPR, MiFID II, Dodd-Frank) and their impact on data management.
- Ability to work independently as well as collaboratively in a team environment.
- Relevant professional certifications (e.g., CFA, FRM) are considered an asset.