Data Operations Tech Lead

Role Overview

• Act as the technical lead for Data Operations, owning the operational readiness of modern data pipelines built on Airflow, Spark, and cloud data infrastructure
• Lead incident triage and resolution for Tier 1 and Tier 2 pipeline issues (data delays, job failures, data quality alerts, SLA breaches)
• Establish clear runbooks, escalation paths, and operational best practices for pipeline support
• Partner with Data Engineering to influence pipeline design with operability, observability, and supportability in mind
• Design and improve monitoring, alerting, and dashboards for data pipelines and workflows
• Implement automation to reduce manual intervention (auto-retries, self-healing workflows, standardized alerts)
• Drive root cause analysis (RCA) and post-incident reviews to prevent recurring issues
• Continuously improve pipeline reliability, performance, and cost efficiency
• Mentor and upskill team members transitioning from SQL Server–centric workflows to Airflow, Spark, ELK stack, and distributed data systems
• Create learning paths, documentation, and hands-on guidance for modern data tooling
• Lead by example with hands-on troubleshooting, debugging, and operational support
• Help establish a culture of ownership, quality, and continuous improvement within Data Operations
• Work closely with Data Engineering, Platform, and Product teams to align on priorities and operational expectations
• Serve as a bridge between legacy data systems and the modern data platform during the transition period
• Provide feedback on operational gaps, tooling needs, and process improvements

Requirements

• 8+ years of experience in data engineering, data platform operations, or data reliability roles
• Hands-on experience operating data pipelines built on Airflow (or similar orchestrators) and Spark
• Strong understanding of distributed data systems, batch processing, and failure modes at scale
• Solid SQL skills and experience working with relational databases (e.g., SQL Server, Postgres)
• Proven experience supporting production data pipelines with SLAs and on-call responsibilities
• Experience with one of the Cloud platforms (AWS, GCP, or Azure)

Tech Stack

• Airflow
• AWS
• Azure
• Cloud
• Google Cloud Platform
• Postgres
• Spark
• SQL

Benefits

• Work from anywhere in the US! Machinify is digital-first.
• Full Medical/Dental/Vision for employees & their families
• Flexible and trusting environment where you’ll feel empowered to do your best work
• Unlimited FTO
• Competitive salary, equity, 401(k) including employer match