Lead, mentor, and grow a team of 6–10 software and data engineers, fostering a culture of collaboration and engineering excellence
Job Summary
Lead, mentor, and grow a team of 6–10 software and data engineers, fostering a culture of collaboration and engineering excellence.
Define and execute the technical roadmap for data processing infrastructure and design and build scalable data pipelines for structured, semi-structured, and unstructured data.
Ensure data quality, reliability, and consistency across pipelines, optimize system performance, and manage infrastructure costs effectively.
Matching Summary
Lead, mentor, and grow a team of 6–10 software and data engineers, fostering a culture of collaboration and engineering excellence.
Skills & Requirements
Must-have
Data processing frameworks (Spark, Kafka, Flink)
Cloud platforms (AWS, GCP, Azure)
Batch and streaming data architectures
Data modeling and schema design
Orchestration tools (Airflow, Prefect)
DevOps and CI/CD pipelines
Nice-to-have
Working with unstructured data
Modern data stack knowledge
AI/ML data pipelines
Vector databases and semantic search
Open-source contributions
Key Requirements
8+ years in data engineering or distributed systems
3+ years in engineering management
Proficiency in Python, SQL, Java/Scala, or Go
Experience with modern data storage formats
Experience with containerization and infrastructure tools