Lead Python/ SQL Database Analytics Engineer

Key Responsibilities:

Platform Design & Development:

Design, architect, and develop backend systems for data ingestion and analytics platforms.

Build and maintain data pipelines to efficiently ingest and store data from both internal and external sources.

Develop quality control processes, monitoring systems, and workflow dashboards.

Technical Expertise:

Work with cloud technologies (AWS, Azure, GCP), Snowflake, Spark, and messaging tools like Kafka.

Develop Python APIs and write complex SQL queries, stored procedures, and functions.

Optimize SQL performance and implement quantitative models and risk analytics.

Leadership & Collaboration:

Lead a team of senior developers, ensuring alignment with team and firm goals.

Collaborate with front-end and back-end engineers, product managers, and business partners.

Participate in strategic discussions and contribute to the overall development roadmap.

Support & Process Improvement:

Support overnight batch jobs and simplify manual data processes.

Enhance cloud data and compute utilization strategies.

What Makes This Role Interesting:

Ground-Level Contribution: Play a pivotal role in building credit analytics platforms from the ground up.

Cross-Functional Exposure: Work closely with portfolio managers, quantitative analysts, and other senior professionals in the investment space.

Opportunities for Growth: Expand your financial knowledge across various asset classes, markets, and instruments.

Basic Qualifications:

Experience:

12+ years in application design, coding, testing, maintenance, and debugging.

5+ years leading a team of senior developers in the financial domain.

Technical Skills:

Proficient in Python, SQL, Java, REST APIs, and Microservices.

Strong experience with cloud technologies (AWS, GCP, Azure), Snowflake, Spark, Kafka, and Git.

Proficient in DevOps tools like Jira, Confluence, Jenkins, and CI/CD pipelines.

Industry Knowledge:

Experience in building data pipelines, designing data models, and working with large-scale financial data.

Familiarity with market data vendors (e.g., Bloomberg, Markit, S&P, ICE) and fixed income asset types (corporate bonds, MBS, CLOs).

Education:

Bachelor's or Master’s degree in Computer Science, Engineering, Physics, Math, or a related field.

Preferred Qualifications:

Experience with security master data systems and working with financial market data vendors.

Expertise in distributed systems and handling large-scale data such as trades, risk, and market data.

Knowledge of financial instruments and fixed income analytics for assets like corporate bonds, Treasuries, and derivatives.

Skills & Competencies:

Analytical Skills: Strong ability to analyze and solve complex problems.

Ownership: Must take full responsibility for projects, from discovery and design to testing and deployment.

Communication: Effective communication skills to work with senior analysts, business partners, and cross-functional teams.

Leadership: Experience leading teams and fostering a collaborative and productive environment.

Self-Starter: Ability to work independently, prioritize tasks, and manage multiple projects.

Documentation: A strong desire to document work and share knowledge for long-term support.

Special Knowledge:

Experience working in the finance industry and handling large-scale, high-volume data.

Expertise in fixed income analytics and security data systems is a plus