We are looking for an Engineering Manager or experienced Team Lead with a strong Data Engineering background to lead and scale the teams building our high-reliability, secure, and linearly scalable Data direction.
This role is ideal for engineering leaders who combine strong technical expertise in data and platform engineering with people leadership and delivery ownership. Whether you are already an Engineering Manager or a hands-on Team Lead looking to expand your impact, you will play a key role in shaping teams, data architecture, and engineering culture.
You will lead the company's transition toward an AI-first approach - ensuring fast, governed access to analytics and AI/ML models while maintaining strict financial and regulatory compliance. You will work at the intersection of data engineering, platform/infrastructure, and business, with a strong focus on reliability, performance, scalability, security, and data governance.
Responsibilities
- Lead and develop cross-functional Data Engineering and Data Platform teams
- Own delivery, quality, and technical outcomes for the data platform
- Partner closely with Product, Analytics, Data Science/ML, and Senior Engineering leadership to translate business and AI requirements into a scalable platform roadmap
- Drive and evolve data engineering processes, including planning, estimation, CI/CD for data, testing and data quality, code reviews, and release management
- Contribute to architectural decisions for data systems running on hybrid infrastructure (batch + streaming, lakehouse, and beyond)
- Ensure high availability, performance, data reliability, and observability of production pipelines and platform services
- Embed security, privacy, data lineage, and regulatory compliance into the platform by design
- Identify and reduce technical and data debt while maintaining delivery velocity
- Mentor engineers, support career growth, conduct 1:1s and performance conversations
- Participate in hiring and team scaling initiatives
- Foster a culture of ownership, collaboration, data quality, customer focus, and continuous improvement
Requirements
- 5+ years of hands-on professional Data Engineering experience, with a strong track record of building and operating production-grade data pipelines and platforms
- Experience leading engineering teams as an Engineering Manager, Team Lead, or similar leadership role
- Strong understanding of modern data architectures, including data modeling, ETL/ELT, distributed data processing, pipeline orchestration, batch and streaming workloads, and data storage
- Experience delivering complex data systems or platforms in production environments
- Background in financial systems, FinTech, or other high-reliability, regulated domains
- Strong understanding of data platform and backend systems - data modeling, distributed data processing, and pipeline orchestration
- Hands-on experience with the modern data stack: batch and streaming processing, orchestration, and warehousing/lakehouse
- Knowledge of CI/CD pipelines, infrastructure automation, and deployment strategies for data workloads
- Familiarity with data observability (data quality, metrics, logging, alerting, lineage) and performance monitoring
Nice to Have
- Experience building platforms that serve AI/ML workloads (feature stores, MLOps, model-serving, vector/embedding stores)
- Experience with low-latency or high-throughput data systems
- Exposure to trading, fintech, or market-data platforms
- Experience with data governance, security, and regulatory compliance (PII handling, audit, lineage) in financial environments
- Experience scaling data and engineering teams and organizations
