Data Engineer II
Description:
Job Description
Data Engineer II
About the Firm
Firm Mission
“Achieving Client Success through Research and Technology”
Los Angeles Capital, the “Firm”, is a global equity manager of assets for leading institutions around the world. The Firm is recognized as a pioneer in dynamic equity management, utilizing proprietary technology to engineer equity portfolios that adapt to today’s equity market. The Firm’s senior investment professionals have worked together for three decades developing models for measuring and forecasting return and risk of global equity securities. The Firm manages approximately $40.1 billion as of December 31, 2025, across a wide variety of public equity strategies designed to meet institutional client return and risk objectives. The Firm has been ranked for seven years in a row by Pensions and Investments as one of the “Best Places to Work in Money Management.” The Firm’s working environment places a strong focus on teamwork and values work-life balance. The Firm offers a competitive compensation package that includes health care plans, 401(k), and top-tier benefits. The Firm is 100% employee-owned through a holding company structure and seeks to retain and motivate employees’ long term. Los Angeles Capital firmly believes the quality and commitment of the individuals are vital to the success of the Firm, ensuring that client expectations are exceeded.
Position Overview
Reporting to the Managing Director, Investment Management Systems, the Data Engineer II will help design, build and deploy the data systems and work with Data APIs, Data Pipeline, Data Lake, ML Ops, etc. The Data Engineer II will help define and build the data tech stack including Snowflake, Databricks, SQL, Python, Prefect, Airflow, dbt, Tableau, MLFlow, and be a key player in enabling the business teams to leverage data to meet business goals.
Key Job Responsibilities
Design, build, and maintain scalable data pipelines and ELT/ETL workflows using Snowflake and Databricks to ingest, transform, and serve data from diverse sources across the firm.
Architect and implement the firm's modern data platform, including data lake and data warehouse layers, with a focus on reliability, performance, and cost efficiency.
Evaluate, select, and implement data orchestration tools (e.g., Apache Airflow, Dagster, Prefect, or similar) to manage workflow scheduling, dependency management, and monitoring.
Build and maintain a comprehensive data catalog that documents datasets, lineage, ownership, and usage across the organization, enabling self-service data discovery.
Develop and enforce a data governance framework including data quality standards, access controls, classification policies, and compliance procedures.
Implement data quality monitoring, validation, and alerting to ensure the integrity and trustworthiness of data assets.
Collaborate with quantitative researchers and portfolio managers to understand data requirements and deliver reliable data products that support investment decision-making.
Create and maintain technical documentation, data dictionaries, runbooks, and architectural diagrams.
Contribute to the evaluation of third-party data vendors and integration of external data sources, including market data, reference data, and alternative data.
Optimize and maintain the Analytics tools environment
Work in agile teams include sprint planning, backlog grooming and program increments.
Mentor and coach data engineers on the team
Skills and Knowledge Required
Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, or a related field
4-6+ years of relevant hands-on experience in data and analytics domain / teams.
Expert level proficiency in SQL
Strong experience with Azure, including core services such as compute, storage, networking, and authentication.
Proficiency with infrastructure-as-code tools, particularly Terraform.
Hands-on experience building and managing CI/CD pipelines using tools such as GitHub Actions or Azure DevOps.
Solid scripting and automation skills in Python, Bash, or similar languages.
Experience with containerization (Docker) and familiarity with orchestration platforms such as Kubernetes or ECS.
Strong understanding of networking, security, and identity management in cloud environments.
Experience with version control workflows in Git, including branching strategies and code review processes.
Demonstrated ability to adapt to new data technologies and learn quickly
Ability to communicate across all levels of the organization and work with diverse project teams
Skills and Knowledge Desired
Experience in the financial services or investment management industry.
Familiarity with market data feeds, reference data systems, and financial data vendors (e.g., Bloomberg, FactSet, MSCI).
Knowledge of data privacy regulations and compliance requirements relevant to financial services.
Experience with cloud infrastructure Azure, including networking, security, and user authentication.
Exposure to dbt for analytics engineering and transformation layer management.
This is a hybrid position based in Los Angeles, CA which requires weekly attendance.
No recruiters, please.
Los Angeles Capital is an SEC registered investment adviser and required to track certain political contributions under rule 206(4)-5. Therefore, you will be required to disclose your prior political contributions.
Los Angeles Capital is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual’s race, color, religion, age, gender, gender identity, sexual orientation, national origin, ancestry, marital status, medical condition, genetic information, veteran status or disability.
For more information about the company, please refer to our website at
Personnel/Applicant Privacy Notice
Los Angeles Capital is committed to safeguarding the privacy of our personnel and job applicants. Los Angeles Capital does not "sell" (as that term is defined in the CCPA) your personal information. Please see our Privacy Policy for details.
Full-time