Drive the development of sophisticated and robust logic and backend infrastructure that supports large-scale data and compute workflows.
Collaborate across teams to design solutions that meet performance, reliability, and security requirements.
Contribute to the automation and optimization of engineering processes, improving deployment velocity and system health.
Participate in the full software development lifecycle, from ideation and design to deployment and monitoring.
Help shape engineering standards, technical architecture, and operational best practices within the team.
Minimum Qualifications:
Bachelor's degree in Computer Science, Computer Engineering, or Electrical Engineering, or a related field from a leading university, or equivalent experience accepted in lieu of degree.
2+ years of professional software engineering experience.
Full proficiency in Python (Go advantage).
Experience with deploying and managing containerized applications using orchestration platforms (Kubernetes, Docker).
Experience with cloud infrastructure platforms (AWS – advantage) and with Linux environments.
Preferred Qualifications:
Experience with event-driven architecture and event processing services, including streaming platforms and message brokers (Kafka, Kinesis, RabbitMQ, Redis).
Experience in modern ETL/ELT frameworks (Airflow, Spark, dbt, Snowflake, AWS Glue) for building scalable data pipelines. Hands-on experience with monitoring tools (Prometheus, Grafana, Datadog), observability platforms (Elasticsearch, Logstash, Kibana, Splunk), and data management systems (OpenMetadata, Datahub, Great Expectations).
Hands-on experience in version control (Git) and CI/CD pipelines (Github Actions, Jenkins) for deploying and maintaining data infrastructure.
Strong advantage – Familiarity with Large Language Models (LLMs) and AI/ML integration in data systems, including familiarity with vector databases model embeddings.
