Lead Engineer, Data Platform
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Job Description
Lead Engineer building secure, scalable hybrid data platforms for a global investment management firm. Leading architecture, automation, reliability, and enterprise data engineering standards.
Responsibilities:
- Own the end-to-end architecture and evolution of the enterprise data platform across hybrid environments
- Set the technical direction, roadmap, standards and reusable patterns for orchestration, scheduling and data processing
- Lead architectural decisions, proofs of concept and adoption plans focused on scalability, security and cost
- Establish reliability, observability and operational standards, including monitoring, alerting, failure recovery and SLOs
- Drive automation through infrastructure as code, CI/CD and automated testing
- Conduct design and code reviews
- Mentor team members and champion a culture of engineering excellence
- Provide a secure, scalable and trustworthy foundation for storing, processing and distributing critical enterprise data across cloud and on-premises environments
Requirements:
- 12+ years of experience in data/platform engineering, designing and operating enterprise-scale data platforms
- Deep, hands-on Snowflake expertise (architecture, ingestion, transformation, workload management, cost, governance)
- Production experience with Apache Airflow and Apache Kafka / event-driven architectures
- Proven ability to integrate batch and streaming pipelines (Snowflake, Airflow, Kafka)
- Advanced Python and SQL
- Terraform, Git, CI/CD
- Experience in regulated environments: security, data quality, access management and compliance
- Proven technical leadership: team direction, mentoring and communication with technical and business stakeholders
- Fluent English, written and spoken
- Java experience for Kafka-based services/connectors is a plus
- OpenShift or Kubernetes experience is a plus
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