About the Role
The role involves developing robust data pipelines, optimizing data storage solutions, and collaborating with analytics and machine learning teams to ensure data accessibility and reliability.
Responsibilities
- Design and implement scalable data processing pipelines
- Maintain and optimize data storage infrastructure
- Ensure data accuracy, consistency, and availability
- Collaborate with machine learning teams on feature engineering
- Support analytics initiatives with reliable datasets
- Troubleshoot and resolve data flow issues
- Improve data pipeline monitoring and alerting
- Participate in code reviews and system design discussions
- Evaluate and integrate new data technologies
- Document data models and pipeline architecture
- Enforce data governance and security standards
- Work with streaming and batch data systems
- Optimize query performance across data platforms
- Support data warehouse operations
- Contribute to disaster recovery planning
- Automate operational data tasks
- Ensure compliance with data privacy regulations
- Assist in capacity planning for data growth
- Integrate third-party data sources
- Promote best practices in data engineering
Nice to Have
- Master’s degree in a technical field
- Experience with machine learning pipelines
- Contributions to open-source data projects
- Knowledge of Kubernetes
- Experience with Apache Kafka
- Familiarity with data mesh architectures
- Certifications in cloud data services
- Background in high-scale data environments
- Experience with data observability tools
- Leadership in technical projects
Compensation
Competitive salary with performance bonuses
Work Arrangement
Hybrid remote
Team
Cross-functional team with data scientists, analysts, and software engineers
Technology Stack
- Primary languages: Python, SQL
- Big data platforms: Spark, BigQuery
- Cloud infrastructure: Google Cloud Platform
- Orchestration: Airflow
- Data storage: Parquet, Avro, Cloud Storage
Work Environment
- Flexible working hours
- Remote-first culture with team meetups
- Emphasis on work-life balance
- Collaborative team atmosphere
Professional Development
- Annual learning budget
- Access to technical conferences
- Internal knowledge-sharing sessions
- Mentorship opportunities
Available for qualified candidates
