Description

You will lead the design and optimization of scalable, high-availability data infrastructure.

Responsibilities

• Design and optimize scalable data infrastructure to ensure high availability and reliability.
• Lead and mentor a team of 5+ Data Engineers.
• Define and execute the data roadmap in collaboration with engineering and analytics teams.
• Ensure data security, governance, and compliance including GDPR and SOC2.
• Optimize data processing workflows for performance and cost efficiency.

Required Skills

• 10 to 18 years of experience in Data Engineering or Software Engineering.
• 3+ years of leadership experience managing a team of 5+ Data Engineers.
• 8+ years of backend coding experience in Java, Python, Node.js, or GoLang.
• Expertise in large-scale distributed architectures using Kafka, Spark, Hive, and Hadoop.
• Hands-on experience with HDFS, YARN, Map-Reduce, Airflow, and Presto.
• Proficiency with NoSQL databases including Redis, Cassandra, MongoDB, or TiDB.
• Experience with cloud platforms such as AWS, GCP, or Azure.
• Proven ability in HLD and LLD for designing scalable data solutions.
• Background working in B2B SaaS companies or high-data-traffic analytics products.

Preferred Skills

• Experience in Machine Learning Infrastructure (MLOps) and real-time data streaming pipelines.
• Familiarity with DevOps tools including Jenkins, Docker, Kubernetes, Grafana, and ELK.
• Prior experience in high-growth SaaS, fintech, or analytics-driven companies.

Key Skills

Education

Any Gradute