招聘
Pay range:
USD $157,000.00 - $205,000.00 / Year
Your opportunity
At Schwab, you're empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us "challenge the status quo" and transform the finance industry together.
We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s).
The SAMDA Investment Data Domain Tech Lead is the hands-on technical leader responsible for the design, implementation, and technical quality of investment data products and Data APIs delivered on the SAMDA platform.
This role owns the day-to-day technical execution of investment-domain data pipelines,operational data stores, domain models, and data service interfaces, ensuring solutions are production-ready, compliant, and aligned with platform standards. The Tech Lead works closely with domain platform leads, platform engineering, governance, and consumer teams to translate investment, regulatory, and operational requirements into scalable data foundations and reliable data services.
In addition to domain execution, the Tech Lead proposes, designs, and helps create reusable data platform capabilities that scale across the broader SAM data platform, enabling consistent reuse across multiple investment domains.
This role is deeply hands-on, with accountability for data correctness, domain fidelity, API reliability, and operational readiness, rather than overall program or platform ownership.
Key Responsibilities Investment Data Foundations
- Lead the design and implementation of investment data models and operational data stores, built from the ground up to support regulatory, operational, and analytical use cases.
- Design foundational operational data stores(e.g., source-aligned stores, connected data stores, and domain-level aggregates) that enable consistent and scalable data consumption across investment workflows.
- Define and own investment data taxonomy, including canonical definitions, naming standards, entity relationships, and domain semantics across holdings, positions, transactions, accounting, and reference data.
- Apply deep investment-domain knowledge (e.g., IBOR, ABOR, custody, holdings, positions, transactions, security and product reference data) to ensure models accurately represent real-world investment behavior and lifecycle events.
- Ensure data models are designed for long-term extensibility, supporting new products, strategies, custodians, and regulatory requirements without re-architecture.
- Partner with Data Governance and Architecture teams to align domain models with enterprise data standards, classification, lineage, and quality expectations.
- Balance domain-specific fidelity with platform-wide consistency, avoiding bespoke or siloed designs.
- Review and approve data design artifacts to ensure clarity, correctness, and operational usability prior to production release.
Data API Design & Delivery (API-Focused)
- Lead the design and delivery of Data APIs that expose investment-domain data as reliable, well-defined services for downstream consumers.
- Define and enforce API best practices, including contract clarity, schema discipline, versioning, and backward compatibility, enabling safe evolution over time.
- Ensure APIs meet expectations for availability, performance, security, and operational supportability.
- Drive API documentation, discoverability, and onboarding for internal consumers.
- Partner with platform teams to ensure APIs integrate cleanly into the broader SAMDA ecosystem.
- Contribute to the development and standardization of shared API patterns and reusable components.
Scalable Data Capabilities & Platform Leverage
- Propose and design reusable data capabilities that address investment-domain needs while scaling across the broader SAMDA platform.
- Identify patterns and abstractions from domain implementations that can be generalized and reused across multiple SAM data domains.
Partner with Platform Engineering and Architecture to:
- Validate scalability and reusability
- Align solutions with long-term platform direction
- Avoid domain-specific point solutions where shared capabilities are appropriate
- Contribute domain-driven enhancements back into shared data frameworks, models, and APIs.
- Escalate design trade-offs when domain requirements conflict with platform consistency.
Platform Alignment, Security & Governance
- Ensure all investment data and Data APIs comply with platform standards, data classification rules, information barriers, and governance expectations.
- Support architecture, risk, and governance reviews by providing clear data models, taxonomy definitions, lineage explanations, and API contracts.
- Identify gaps in platform data or API capabilities and recommend improvements.
Operational Readiness & Production Support
- Own technical production readiness for investment-domain data assets and APIs, including:
- Monitoring and alerting readiness
- SLA alignment
- Incident triage and root-cause analysis
- Ensure runbooks, dashboards, and operational documentation are accurate and current.
- Partner with Platform Engineering and SRE teams to continuously improve stability, observability, and resilience.
Delivery Leadership & Team Enablement
- Provide hands-on technical leadership to engineers delivering investment-domain data and APIs.
- Break down complex domain requirements into clear, actionable technical work.
- Mentor engineers on data modeling discipline, taxonomy, and service quality.
- Maintain high engineering standards through design reviews and code walkthroughs.
Continuous Improvement
- Identify opportunities to improve data quality, model clarity, performance, and operational robustness.
- Reduce technical debt and operational risk across the investment data domain.
- Proactively improve alignment between domain delivery and platform evolution.
What you have Required Qualifications & Experience
- 8-12+ years of experience in data engineering, data architecture, or platform-aligned engineering roles.
- Proven ability to design operational data stores and domain models from scratch in enterprise environments.
- Deep experience delivering investment, accounting, custody, or regulatory data on shared data platforms.
- Hands-on experience designing and operating Data APIs in production environments.
- Strong understanding of investment data domains including holdings, positions, transactions, IBOR, ABOR, and reference data.
- Experience working in regulated, enterprise environments with strong governance and risk controls.
Preferred Qualifications
- Experience with cross-product investment data models and federated data ownership.
- Strong familiarity with enterprise data taxonomy, lineage, and governance practices.
- Experience supporting operational and regulatory investment use cases at scale.
- Strong operational mindset with production support experience.
- Comfort collaborating with architects, governance teams, and senior stakeholders.
What's in it for you
At Schwab, you're empowered to shape your future. We champion your growth through meaningful work, continuous learning, and a culture of trust and collaboration-so you can build the skills to make a lasting impact. Our Hybrid Work and Flexibility approach balances our ongoing commitment to workplace flexibility, serving our clients, and our strong belief in the value of being together in person on a regular basis.
We offer a competitive benefits package that takes care of the whole you - both today and in the future:
- 401(k) with company match and Employee stock purchase plan
- Paid time for vacation, volunteering, and 28-day sabbatical after every 5 years of service for eligible positions
- Paid parental leave and family building benefits
- Tuition reimbursement
- Health, dental, and vision insurance
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关于Charles Schwab

Charles Schwab
PublicCharles Schwab Corporation is a major American multinational financial services company that provides brokerage, banking, and financial advisory services to individual and institutional clients.
10,001+
员工数
Westlake
总部位置
$134B
企业估值
评价
4.3
10条评价
工作生活平衡
4.2
薪酬
3.8
企业文化
4.1
职业发展
3.2
管理层
4.4
78%
推荐给朋友
优点
Supportive management
Great work-life balance and flexibility
Excellent benefits and pay
缺点
Slow promotion and limited career advancement
Demanding work hours and fast-paced environment
Bureaucratic processes
薪资范围
29个数据点
L2
L3
L4
L5
L6
Mid/L4
Senior/L5
L2 · Financial Analyst L2
0份报告
$102,538
年薪总额
基本工资
$41,015
股票
$51,269
奖金
$10,254
$71,777
$133,299
面试经验
7次面试
难度
3.0
/ 5
时长
14-28周
录用率
28%
体验
正面 14%
中性 58%
负面 28%
面试流程
1
Phone Screen
2
Interview
3
Background Check
常见问题
Phone Interview
Recruiter Screening
Technical Assessment
新闻动态
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1d ago
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·
2d ago