Data Engineer

Nimble GravityRemote - LATAM (Remote)+ Equity1w ago

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Requirements

Education & Certificates
A bachelor's degree or higher in a STEM field, required
Concentration in Computer Science, Math, Physics or other engineering related field, preferred
5+ years of experience in data engineering or a related discipline, with a proven track record of success.
Experience in the financial services or private equity industry, preferred
Competencies & Attributes
Expertise in Python and SQL, with a strong foundation in data manipulation and analysis.
Proficient with Databricks/PySpark and dbt for data warehousing and data transformation tasks.
Experience with workflow orchestration tools e.g. Airflow, Temporal
Experience working with large language models (LLMs) especially prompt engineering, retrieval-augmented generation (RAG)s, and/or vector databases.
Knowledge of fundamental principles of machine learning, feature engineering, and knowledge graphs are pluses.
Demonstrated experience in designing and implementing complex data systems from the ground up.
Proficient in handling large-scale data projects, including data cleaning, ETL, and information retrieval.
Previous experience in a product development or financial services environment is highly desirable.
Excellent communication skills required, both verbal and written.
Nimble Gravity is a team of outdoor enthusiasts, adrenaline seekers, and experienced growth hackers. We love solving hard problems and believe the right data can transform and propel growth for any organization.

Build, scale, and maintain robust data solutions to support the firm's objectives.
Implement and optimize high-performance data pipelines: extraction, loading, transformation, and orchestration – that are designed for scalability, reliability, maintainability, and speed.
Lead software development projects end to end involving large language models (LLMs), retrieval-augmented generation (RAG) frameworks, and other AI technologies.
Champion modern software engineering practices as CI/CD, infrastructure-as-code, containerization, and cloud-native deployments
Collaborate closely with business stakeholders to transform use cases into production-ready services and solutions, owning the system from concept to production.
Implement rigorous testing and monitoring practices to maintain superior data quality and integrity.
Mentor and develop junior team members, fostering a culture of excellence and continuous learning within the team.
Be willing to travel up to 20% of the time to collaborate with distributed team members across locations.