About the Role
The role involves building and optimizing data pipelines, ensuring data accuracy and accessibility, and supporting analytics initiatives across departments through robust engineering practices.
Responsibilities
- Design and implement scalable data pipelines for ingestion, transformation, and storage
- Optimize data workflows for performance and reliability
- Collaborate with analytics and product teams to understand data needs
- Ensure data quality and consistency across systems
- Maintain and improve existing data architecture
- Monitor data pipeline health and resolve issues proactively
- Support compliance with data governance policies
- Document data models, schemas, and integration processes
- Evaluate and integrate new data technologies
- Work with distributed systems and cloud-based data platforms
- Troubleshoot data delivery issues across pipelines
- Implement data validation and testing frameworks
- Support data warehouse development and maintenance
- Contribute to capacity planning for data infrastructure
- Participate in code reviews and system design discussions
- Drive best practices in data engineering and automation
- Scale data systems to meet growing business demands
- Ensure secure handling and access controls for sensitive data
- Collaborate on real-time data processing solutions
- Assist in defining data strategy and roadmap
- Improve observability of data operations
- Integrate third-party data sources securely
- Mentor junior engineers and share technical knowledge
- Stay current with advancements in data technologies
- Support incident response related to data systems
Nice to Have
- Master’s degree in computer science or related field
- Experience with machine learning pipelines or data science workflows
- Contributions to open-source data projects
- Experience in regulated industries such as finance or healthcare
- Leadership experience in data platform modernization
- Certifications in cloud data technologies
- Hands-on work with data mesh or domain-driven data architectures
- Knowledge of data contract frameworks
- Experience with data observability platforms
- Prior work in high-growth technology environments
Compensation
Competitive salary and benefits package
Work Arrangement
Hybrid work model with flexibility for remote and office-based work
Team
Collaborative engineering team focused on data infrastructure and analytics
About the Team
This role is part of a high-performing data engineering group that powers analytics and machine learning across the organization. The team values technical excellence, collaboration, and continuous improvement.
Technology Stack
The team uses modern cloud-native tools including GCP, BigQuery, Apache Airflow, Kafka, and Kubernetes. Infrastructure is managed through IaC with Terraform and deployed via CI/CD pipelines.
Growth Opportunities
Engineers are encouraged to lead initiatives, present technical designs, and contribute to architectural decisions. Career paths support both individual contributor and leadership tracks.
Work Culture
The environment emphasizes ownership, transparency, and learning. Regular tech talks, hackathons, and training support professional development.
Onboarding Process
New hires receive structured onboarding including system walkthroughs, mentorship, and hands-on projects to accelerate ramp-up.
Available for qualified candidates
