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About the Role

As a Data Engineer Lead, you will set the technical direction for the data platform and data products that power portfolio construction, investment research, and monitoring capabilities for the Capital Solutions Group. This is a senior, hands-on individual contributor role where you will write code, own architecture and delivery, and partner closely with investment group, product management, and technology leaders. You will be a leader in our AI-first engineering practices, building the trusted data foundation that AI applications need to answer complex investment questions. You have an agile mindset and will lead the design, implementation, and delivery of large-scale, critical, and complex data architecture, storage, and pipelines.

Responsibilities

Set the data engineering strategy and roadmap for CSGT, including the Lakehouse architecture on Databricks and AWS.
Make and explain decisions on scalability, security, reliability, and cost, and influence standards and practices across adjacent teams and the wider Capital Group technology organization.
Design and build ingestion, transformation, and serving pipelines with Databricks, PySpark, Delta Lake, dbt, and Airflow, and create reusable patterns and frameworks.
Analyze new structured and unstructured datasets at the business-capability level and fit them into the platform’s data domains and subject areas.
Own delivery of complex, cross-team data initiatives from requirements through production support, including estimates, work breakdown, sequencing, dependencies, and cost.
Surface risks early and balance immediate business needs with a durable platform.
Lead the continued evolution of AI-first engineering: turn business outcomes into well-defined specifications, engineer the business, architectural, and repository context agents need, and direct agents to plan, build, test, and document changes.
Build reusable agent workflows, skills, and tool integrations for data engineering work.
Define which actions agents can take on their own, which require human approval, and how agent activity is reviewed and traced.
Make data understandable and reliable for AI through curated Unity Catalog metadata, lineage, business definitions, semantic models, and access controls.
Connect data to Databricks Genie and other AI applications used by investment professionals.
Define evaluation datasets and acceptance criteria for agents and AI-generated SQL and code.
Define the testing strategy across all layers of the platform, including performance, stability, and availability.
Review and approve quality metrics before release.
Build data quality, reconciliation, freshness, observability, and recovery controls into automated testing and CI/CD, with security and policy checks embedded from the start.
Partner with investment professionals and product managers to develop a shared product vision and ownership of business outcomes.
Demonstrate how data and AI can scale research and portfolio construction.
Lead design and code reviews, direct the day-to-day work of engineers on your initiatives, and guide them through the most complex data and performance issues.
Teach engineers to inspect and challenge AI-generated work, share reusable patterns and context through internal and external forums, and help managers identify strengths and development needs.

Requirements

10+ years of experience in data or software engineering, including technical leadership of complex production data platforms delivered across multiple teams.
Strong hands-on Python and SQL skills, sound software design judgment, and a deep understanding of distributed data processing, query performance, and automated testing.
Production experience with Databricks on AWS, including PySpark, Delta Lake, Unity Catalog, Databricks Jobs, Databricks SQL, and Databricks Asset Bundles.
Understand the security, access, and cost implications of your designs.
Orchestrated production pipelines with Apache Airflow (including Astronomer) and built tested transformations with dbt, with reliable retries, backfills, and dependency management.
Strong data modeling and governance experience, including dimensional and time-series models, slowly changing dimensions, bi-temporal history, data contracts, lineage, and semantic metadata.
Implemented data quality, observability, and CI/CD for data platforms using tools such as Deequ, dbt tests, Lakehouse Monitoring, Datadog, Terraform, and Harness.
Experience preparing governed data for AI through natural-language-to-SQL tools such as Databricks Genie, semantic metadata, or other governed data-access patterns.
Use AI coding agents well beyond code completion: writing specifications, supplying context, running tests, and reviewing generated changes through source control.
Evaluate AI-generated output with representative test cases, regression tests, execution traces, and human review.
Distinguish a plausible answer from a verified one.
Understand prompt injection, sensitive data handling, and least-privilege access.
Design approval boundaries and audit trails for agents working against enterprise systems.
Lead architecture discussions, influence without formal authority, develop other engineers, and explain technical choices and trade-offs clearly to investment professionals and technology leaders.
An agent of change with a sense of urgency: question how work gets done and remove or automate what does not add value, while respecting what came before.
Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.

Skills

Python
SQL
Databricks
AWS
PySpark
Delta Lake
Unity Catalog
Databricks Jobs
Databricks SQL
Databricks Asset Bundles
Apache Airflow
Astronomer
dbt
Data Modeling
Data Governance
Dimensional Models
Time-series Models
Slowly Changing Dimensions
Bi-temporal History
Data Contracts
Data Lineage
Semantic Metadata
Deequ
dbt tests
Lakehouse Monitoring
Datadog
Terraform
Harness
Databricks Genie
Natural-language-to-SQL
AI Coding Agents
Prompt Injection
Sensitive Data Handling
Least-Privilege Access
Investment Management Data
Portfolio Construction
LLM Applications
Agent Workflows
Model Context Protocol (MCP)
PostgreSQL
SQL Server
Lakebase

Location

Southern California
New York

Work Type

Flexible work options

Experience Level

Senior
Technical leadership

Education Level

Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.

Salary/Compensations

Southern California Base Salary Range: $201,683-$322,693
New York Base Salary Range: $213,795-$342,072

Benefits

Competitive salary
Bonuses
Benefits
Company-funded retirement contribution
Generous time-away
Health benefits from day one
Opportunity for flexible work options
2-for-1 matching gifts for charitable contributions
Opportunity to secure annual grants for organizations
On-demand professional development resources
Individual annual performance bonus
Capital’s annual profitability bonus
Retirement plan where Capital contributes 15% of your eligible earnings

About the Company

At Capital Group, the success of the people who invest with us depends on the people in whom we invest. That’s why we offer a culture, compensation and opportunities that empower our associates to build successful and prosperous careers. Through nine decades, our goal has been to improve people’s lives through successful investing. We know that our history is a testament to the strength of the people we hire. More than 9,000 associates in 30+ offices around the world help our clients and each other grow and thrive every day.

Equal Opportunity

We are an equal opportunity employer, which means we comply with all federal, state and local laws that prohibit discrimination when making all decisions about employment.
As equal opportunity employers, our policies prohibit unlawful discrimination on the basis of race, religion, color, national origin, ancestry, sex (including gender and gender identity), pregnancy, childbirth and related medical conditions, age, physical or mental disability, medical condition, genetic information, marital status, sexual orientation, citizenship status, AIDS/HIV status, political activities or affiliations, military or veteran status, status as a victim of domestic violence, assault or stalking or any other characteristic protected by federal, state or local law.