Job Summary :

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.

Key Responsibilities :

- Design, build, and maintain scalable big data pipelines and architectures to support robust data solutions.

- Collaborate with cross-functional teams to understand and deliver on data requirements and business objectives.

- Implement data integration, transformation, and processing solutions using Python and relevant big data technologies.

- Develop, manage, and optimize distributed databases and storage systems for efficiency and reliability.

- Monitor, troubleshoot, and enhance data systems to ensure high availability and performance.

- Enforce data quality, security, and governance standards across all solutions.

- Document solutions and communicate complex technical concepts effectively, both in writing and verbally.

Required Skills and Qualifications :

- Proven expertise in big data engineering with hands-on experience building and maintaining large-scale data pipelines.

- Advanced proficiency in Python for data processing, automation, and integration.

- Deep understanding of relational and NoSQL databases, including optimization and management techniques.

- Experience with distributed data processing frameworks (e.g., Hadoop, Spark, Flink).

- Strong foundation in data modeling, ETL processes, and data warehousing principles.

- Excellent written and verbal communication skills, with the ability to convey technical ideas clearly to both technical and non-technical stakeholders.

- Detail-oriented, proactive, and self-motivated, thriving in remote and autonomous work environments.

Preferred Qualifications :

- Prior experience in fast-paced or startup-like environments supporting global teams.

- Expertise with cloud-based big data platforms (e.g., AWS, GCP, Azure).

- Familiarity with machine learning operations and data science workflows is a plus.