Senior Software Engineer - Data Engineering

MoEngage is looking for a talented Senior Software Engineer - Data Engineering to join our team. If you have a proven track record in managing data infrastructure and pipelines on high-scale distributed systems, expertise in programming languages like Java or Python, and experience with cloud environments, you'll be instrumental in building and optimizing our data ecosystem.

Key Requirements

• Experience: A minimum in the data engineering field, demonstrating a track record of managing data infrastructure and pipelines on high scale distributed systems.
• Programming Skills: Expertise in at least one high-level programming language, with a strong preference for candidates proficient in Java and Python.
• Cloud Infrastructure: Proven experience in setting up, maintaining, and optimizing data infrastructures in cloud environments, particularly on AWS or Azure.
• Tech Stack Proficiency: Hands-on experience with a variety of data technologies including, but not limited to:
• Kafka for stream-processing
• Kubernetes for container orchestration
• AWS S3, Athena, and Glue for storage and ETL services
• Spark for large-scale data processing
• Debezium for change data capture
• Apache Airflow for workflow management
• Any one Streaming frameworks (Kstream/Flink/Samza/Spark streaming)
• Data Processing: Demonstrable skills in cleansing and standardizing data from diverse sources such as Kafka streams and databases.
• Query Optimization: Proficient in optimizing queries to achieve optimal performance with large datasets, minimizing processing times without sacrificing quality.
• Problem-Solving Abilities: An analytical mindset with robust problem-solving skills, essential for identifying and addressing issues during data integration and schema evolution.
• Cost Optimization Expertise: A keen eye for cost-saving opportunities without compromising on system efficiency. Capable of architecting solutions that are not only robust and scalable but also cost-effective, ensuring optimal resource utilization and avoiding unnecessary expenses in the cloud and data processing environments.