Lead Data Engineer

Accountabilities • Architect, build, and scale robust data pipelines and infrastructure supporting both AI products and operational applications.

• Design and maintain data ingestion, transformation, processing, and storage architectures for batch and real-time workloads.

• Develop scalable systems for vector search, retrieval, and machine-learning data workflows.

• Build and optimise data models, distributed processing systems, and large-scale query infrastructure.

• Establish frameworks for data reliability, quality, security, governance, monitoring, and observability.

• Collaborate with AI and backend engineering teams to support model training, inference, and data-driven product capabilities.

• Contribute to technical architecture decisions, engineering standards, and the long-term data strategy.

• Partner with founders and product leadership to translate data capabilities into meaningful product and business decisions.

• Take ownership as the founding data specialist, helping define the team’s technical culture, standards, processes, and future hiring requirements.

Requirements

• 7+ years of professional experience, with significant experience in dedicated data engineering roles and ownership of complex data infrastructure.

• Strong experience designing and building scalable data pipelines and distributed data systems.

• Solid experience with relational databases, preferably PostgreSQL; experience with MySQL or comparable technologies is also relevant.

• Experience working with NoSQL databases and modern vector databases used in AI applications.

• Strong Python programming skills, including experience with data-processing libraries such as Pandas or Polars.

• Demonstrated ability to make, communicate, and justify architectural decisions rather than simply implementing predefined solutions.

• Experience building scalable backend systems and designing robust data models and storage architectures.

• Strong understanding of data processing performance, scalability, and optimisation.

• Experience with technologies such as Apache Spark, Apache Airflow, Kafka, Elasticsearch, or OpenSearch is highly desirable.

• Experience with PostgreSQL, MongoDB, and vector technologies such as Qdrant, Milvus, or pgvector is highly desirable.

• Strong collaboration and communication skills, with the ability to work effectively with technical and non-technical stakeholders.

• Experience in AI/ML platforms, event-driven architectures, cloud infrastructure, or high-growth startup environments is a plus.

Benefits

• Remote-first working environment from locations across India.

• Opportunity to take significant ownership as the first senior data engineering hire.

• High-impact role working at the intersection of data engineering, AI, and intelligent automation.

• Direct collaboration with AI engineers, backend engineers, product teams, founders, and leadership.

• Opportunity to shape the data architecture, engineering standards, culture, and future team.

• Exposure to modern technologies including real-time data pipelines, vector databases, machine-learning infrastructure, and distributed systems.

• Strong opportunities for professional growth and technical leadership in a rapidly evolving environment.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?

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