About the Role
This position leads the development and governance of data architecture strategies, ensuring systems are built for scalability, integrity, and operational efficiency while guiding engineering teams through complex technical challenges.
Responsibilities
- Define and maintain enterprise-wide data architecture standards and best practices
- Lead the design of scalable data pipelines and storage solutions
- Collaborate with cross-functional teams to integrate data systems across platforms
- Evaluate and introduce new data technologies and frameworks
- Ensure data consistency, quality, and accessibility across systems
- Mentor engineers in data modeling, database design, and system integration
- Drive architectural decisions for large-scale data processing systems
- Oversee data governance and metadata management initiatives
- Optimize data workflows for performance and reliability
- Support compliance with data privacy and security policies
- Troubleshoot complex data infrastructure issues
- Establish monitoring and alerting for data pipelines
- Promote reuse of data assets and reduce redundancy
- Lead technical documentation for data architecture components
- Facilitate data strategy alignment across business units
- Evaluate third-party data tools and vendors
- Design for fault tolerance and disaster recovery in data systems
- Ensure solutions meet scalability demands over time
- Collaborate with product teams to understand data requirements
- Drive adoption of cloud-based data platforms
- Balance innovation with technical debt management
- Implement data lineage and auditability features
- Guide migration from legacy to modern data architectures
- Foster collaboration between engineering and data science teams
- Contribute to long-term technology roadmaps
Nice to Have
- Advanced degree in computer science or related field
- Experience leading data architecture at enterprise scale
- Public speaking or published work in data engineering domains
- Contributions to open-source data projects
- Certifications in cloud data platforms
- Experience with data mesh or domain-driven data architectures
- Knowledge of machine learning data pipelines
- Familiarity with regulatory frameworks like GDPR or HIPAA
- Leadership in incident response for data systems
- Experience with data observability tools
Compensation
Competitive salary and benefits package
Work Arrangement
Hybrid work model with flexibility for remote and office-based collaboration
Team
Collaborative engineering team focused on scalable data systems and long-term platform evolution
Technology Stack
- AWS, GCP, or Azure cloud infrastructure
- Apache Spark, Flink, or similar processing engines
- Snowflake, BigQuery, or Redshift
- Kafka or other event streaming platforms
- Terraform or equivalent infrastructure tools
- Prometheus, Grafana, or data observability platforms
Leadership Expectations
- Set technical direction for data platform evolution
- Mentor engineers across multiple teams
- Drive consensus on architectural standards
- Represent data engineering in executive discussions
- Balance innovation with system stability
Available for qualified candidates requiring sponsorship
