About the Role
Lead the design and implementation of advanced data analytics systems while driving innovation, setting technical standards, and supporting engineering teams in delivering high-impact data solutions.
Responsibilities
- Define long-term data architecture strategies aligned with business goals
- Oversee development of scalable data pipelines and analytics platforms
- Mentor engineers in best practices for data modeling and processing
- Evaluate and integrate emerging data technologies into existing workflows
- Ensure data accuracy, security, and compliance across systems
- Lead technical discussions and architecture reviews with cross-functional teams
- Drive adoption of automation and monitoring across data operations
- Collaborate with product teams to translate business needs into technical designs
- Optimize query performance and data storage efficiency
- Establish standards for data quality and metadata management
- Support deployment of machine learning models in production environments
- Guide cloud infrastructure decisions for data platform scalability
- Promote reusable components and shared data services
- Troubleshoot complex system issues across distributed environments
- Contribute to technical roadmaps and capacity planning
Nice to Have
- PhD in computer science or related discipline
- Experience scaling data platforms across global organizations
- Contributions to major data processing frameworks
- Public speaking at industry conferences on data topics
- Hands-on experience with MLOps pipelines
- Leadership in open-source data communities
- Prior role as chief architect or CTO in tech-focused company
Compensation
Competitive salary with performance bonuses and equity options
Work Arrangement
Hybrid remote with office availability in major cities
Team
Collaborative engineering unit focused on data platforms and analytics innovation
Technology Stack
- Primary use of Python, Spark, and Airflow for data orchestration
- Cloud infrastructure on AWS with Redshift, S3, and Lambda
- Monitoring via Datadog and ELK stack
- CI/CD pipelines using GitHub Actions and Jenkins
- Adoption of dbt for analytics engineering workflows
Growth Opportunities
- Path to influence enterprise-wide data strategy
- Opportunities to lead research initiatives in data science
- Support for publishing technical work and conference attendance
- Mentorship roles in internal upskilling programs
- Involvement in acquisition and integration of data startups
Work Environment
- Quarterly in-person team gatherings across regions
- Flexible work hours with core collaboration windows
- Dedicated time for innovation and technical exploration
- Employee resource groups for underrepresented technologists
- Internal knowledge-sharing forums and tech talks
Available for qualified candidates requiring relocation support
