Team Lead, Field Engineer
Leads and mentors field engineers while delivering complex client integrations, data pipelines, and automation solutions. The role requires 8+ years of engineering experience, advanced Python, Databricks and Spark expertise, and strong client-facing leadership.
About the job
Responsibilities
- Provide functional leadership and daily operational guidance to field engineers while contributing hands-on to complex engagements.
- Architect, build, and deliver custom integrations, automations, and data pipelines using APIs, ADX, Databricks, and modern engineering tools.
- Allocate team work and coordinate simultaneous client engagements with cross-functional partners.
- Guide issue resolution, escalate blockers, and maintain alignment with clients and internal stakeholders.
- Design production-grade solutions that improve client onboarding, reduce time-to-value, and enable operational scale.
- Build AI, LLM, and machine-learning automation for data transformation, validation, and reconciliation.
- Own ADX implementations and design data infrastructure in Databricks for client onboarding and analytics.
- Write and review production-quality Python for ETL pipelines, API integrations, validation frameworks, and automation tooling.
- Translate ambiguous client requirements into scalable solutions through discovery, prototyping, and iterative delivery.
- Mentor engineers, provide feedback, and support career development.
- Improve tools, workflows, automation, internal frameworks, and delivery best practices.
- Collaborate with Product, Engineering, and Services on productization and platform roadmap opportunities.
- Advise clients and identify opportunities to deliver additional value.
Requirements
- 8+ years of experience in software engineering, data engineering, or forward-deployed technical roles.
- Experience guiding, mentoring, or leading engineers.
- Advanced Python proficiency, including production applications, APIs, and data pipelines.
- Strong understanding of REST APIs, authentication patterns, and integration architecture.
- Hands-on Databricks, Spark, and distributed data-processing experience.
- SQL proficiency and experience with large-scale relational and NoSQL datasets.
- Experience designing ETL/ELT pipelines for complex transformations.
- Familiarity with AI/ML tools and LLM-driven automation.
- Understanding of financial data domains, including portfolio management, performance analytics, and multi-asset-class portfolios.
- Experience with Git, CI/CD pipelines, and modern software-development practices.
- Strong communication and technical presentation skills.
- Ability to prioritize and manage multiple client engagements in ambiguous, fast-paced environments.
- Player-coach mindset with interest in developing people-management skills.
- Organized, adaptable, entrepreneurial, and focused on client impact and quality.
Skills
Python, REST APIs, Databricks, Spark, SQL, NoSQL, ETL, ELT, Machine Learning, LLMs, Git, CI/CD, APIs, Data Pipelines, Authentication
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