Manager, MTS

We are looking for a powerhouse Engineering Manager who hasn't lost their love for code. As a first-level manager, you will bridge the gap between high-level strategy and deep-dive technical execution. You will lead, mentor, and grow a talented team of engineers while remaining actively hands-on (approx. 50% management/architecture and 50% coding/code reviews). The ideal candidate is a veteran engineer with over a decade of experience, possessing a robust background in building scalable Data Engineering pipelines coupled with strong Java backend fundamentals.

Responsibilities

Lead, mentor, and inspire a team of 5–8 data and backend engineers, fostering a culture of high performance and continuous learning; Own the end-to-end delivery of your team's roadmap using Agile/Scrum methodologies; Conduct regular 1-on-1s, set performance goals, and provide constructive feedback to help your engineers grow; Design and implement scalable, robust data pipelines and backend services; Actively participate in coding, code reviews, and architectural discussions to ensure high-quality, maintainable code; Seamlessly blend large-scale data processing systems with robust Java-based microservices.

Requirements

10+ years of total experience in software engineering, with at least 1–2 years in a formal or informal leadership role (Team Lead/Tech Lead/Manager); Proven track record building big data pipelines using technologies like Spark, Hadoop, Kafka, Flink, or cloud-native data warehouses (Snowflake, BigQuery, Redshift); Strong, production-grade experience in Java (8+) and frameworks like Spring Boot for building scalable backend services/microservices; Deep understanding of SQL/NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra) and data warehousing concepts; Familiarity with containerization and orchestration (Docker, Kubernetes); Experience managing CI/CD pipelines (Jenkins, GitLab CI); Currently based in, or willing to relocate to, Bangalore.

Nice to have

Experience on migration projects or tech transformation on Cloud platforms (AWS, GCP, or Azure)