VaR Analytics Engineer

Our client is a dynamic, global financial services firm known for our innovative approach and focus on client service across capital markets, advisory, asset management, and research. We are seeking a skilled Risk Data Analytics Engineer to enhance our data infrastructure, supporting our strategic initiatives in risk management, analytics, and reporting. This role is integral to our commitment to excellence in technology and data-driven decision-making.

About the Company

A prominent player in the global financial landscape, offering a full suite of services across investment banking, asset management, and wealth management. With a focus on agility, innovation, and a collaborative culture, we emphasize the use of leading-edge technology and data analytics to support our clients. We are driven by a commitment to creating a sustainable impact, working closely with clients ranging from corporations and institutions to governments. Our team is composed of talented, diverse individuals who are dedicated to delivering tailored financial solutions in an ever-evolving market.

Responsibilities:

• Design, develop, and optimize ETL pipelines to extract, transform, and load risk data from various sources into a data warehouse.

• Data Warehousing: Architect and maintain a robust risk data warehouse to support advanced analytics and reporting for both internal and client-facing needs.

• Leverage cloud services, particularly AWS (Redshift, Databricks, Snowflake), to deliver scalable and high-performing data solutions.

• Data Quality Assurance: Implement and monitor data quality checks to ensure accuracy and reliability across the ETL process.

• Analyze and refine the performance of data pipelines and warehouse queries to enhance efficiency and minimize latency.

• Follow industry-leading practices for data governance, privacy, and protection of sensitive information.

• Partner closely with cross-functional teams, including data scientists, risk analysts, and other technical stakeholders, to understand data requirements and deliver solutions aligned with business objectives.

Qualifications:

• Bachelor’s degree in Computer Science, Data Engineering, or a related field.

• Proven experience in data engineering, specializing in ETL processes and data warehousing.

• Proficiency in SQL and Python for data manipulation and analysis.

• Strong knowledge of cloud computing concepts and practical experience with AWS tools (e.g., Redshift, Databricks, Snowflake, S3, Glue).

• Familiarity with data modeling and warehousing methodologies.

• Strong analytical, problem-solving, and interpersonal communication skills.

• Ability to work independently as well as collaboratively within a fast-paced team environment.

Preferred Skills:

• Experience with data visualization tools like Tableau or Power BI.

• Knowledge of data orchestration tools, such as Airflow.

• Familiarity with data quality and profiling tools for enhanced data accuracy.

Please note, If you are a skilled data engineer passionate about risk data management and eager to contribute to a forward-thinking, high-performance team, we encourage you to apply. Join us and become a part of an environment that fosters growth, innovation, and impact in the world of finance.