Data Engineering Manager

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