Job Description - Engineering Ops (Process Engineering)
Role Overview: We are seeking a proactive and automation-focused Engineering Ops professional to join our team. In this Process Engineering role, you will be responsible for monitoring, troubleshooting, and scaling our overnight and weekend Natural Language Processing (NLP) pipelines as well as weekends (weekend shifts will be shared/split among the team). Key Responsibilities:
Process Monitoring & NLP Pipelines: Monitor and troubleshoot parallel NLP processes, ensuring reliable execution during scheduled shifts (including weekend rotations).
Incident Response & On-Call: Lead incident triage, respond promptly to pipeline breakages, and conduct thorough postmortems to continuously improve system reliability.
CI/CD & Pipeline Management: Manage and scale multiple CI/CD pipelines. Understand the existing pipeline structure, spot gaps, and drive DevOps improvements.
Automation: Identify opportunities to automate manual processes and operational workflows by default.
Proactive Communication: Flag issues (breakages, delays) early and keep cross-functional teams informed with prompt, clear, and accurate status updates.
Team & Process Unification: Champion a process-oriented mindset, contributing to the team by driving standardization and unification of operations across the organization.
Required Qualifications & Skills:
Cloud & DevOps: Strong hands-on background across a wide range of AWS services. Solid grasp of core DevOps practices and scalability principles (designing systems that work at both small and large scales).
Containerization: Hands-on experience with Docker, including building, deploying, and managing containerized workloads.
Scripting & Tooling: Proficient in Python, Git, and Bash for automation and building operational tooling.
Database & SQL (Usage Level): Strong proficiency in writing high-performance SQL queries (complex joins, CTEs, window functions). Experience using Amazon Redshift for querying, data validation, reconciliation, and ensuring data quality (engineering/development of Redshift DBs is not required).
Healthcare Domain Knowledge: Strong domain knowledge in Healthcare/Medical Claims data, including claims processing, adjudication, eligibility, provider/member data, ICD/CPT codes, and healthcare reporting requirements.
Analytical Skills: Strong problem-solving abilities with high attention to detail and accuracy when analyzing large-scale datasets.
Soft Skills: Excellent communication skills with the ability to explain technical operational issues to both technical and non-technical stakeholders. Ability to work effectively in fast-paced environments and manage tight deadlines.
