Data Observability Engineer BigeyeMonte CarloDatabandSoda, Azure

Role: Big Eye Monitoring SME

Hyrbid: 3 days in office

Duration: 7 months

Job Requirements:

- 57 years of experience in Data Engineering Data Quality Data Observability or related disciplines.

- Hands-on experience with Bigeye (preferred) or other observability platforms (e.g. Monte Carlo Databand Soda).

- Proficiency with Azure SQL Azure networking concepts authentication patterns and identity management.

- Strong SQL skills and familiarity with data modeling practices.

- Experience designing and implementing CLI tools or automation workflows.

- Understanding of enterprise network security including IP whitelisting firewall behavior and access control best practices.

- Experience working in Agile/Scrum environments and contributing to ADO-based feature delivery.

Key Responsibilities:

- Lead the design and implementation of a secure Azure SQL login flow tailored for Bigeye integrations.

- Define authentication requirements service principals credential handling and connection policies.

- Collaborate with cloud platform and security teams to ensure compliance with Humana standards.

- Configure validate and operationalize initial data sources within the DEV-DOP Bigeye workspace.

- Establish scalable onboarding patterns to support future additions of datasets and pipelines.

- Build templates or documentation to streamline future data source integration.

- Design and document the Bigeye CLI workflow including command structures automation patterns and usage guidelines.

0 Support engineering teams in implementing CLI-based automation for data monitoring alerting and metadata management.

- Recommend enhancements to the CLI workflow scripting and DevOps integration points.

- Ensure Bigeye connectivity crawlers APIs and ingestion services operate successfully within Humanas IP whitelisted environment.

- Partner with networking and security teams to validate inbound/outbound whitelisting requirements.

- Lead troubleshooting efforts for latency access failures or blocked traffic related to IP restrictions.

- Establish best practices for dataset monitoring anomaly detection SLA validation and automated alert management.

- Create and maintain runbooks for onboarding troubleshooting and recurring operational tasks.

- Mentor engineering teams on data observability principles and Bigeye feature adoption.

- Collaborate closely with Data Engineering Cloud Operations Platform Security and Analytics teams.

- Participate in Agile ceremonies provide story estimates and refine acceptance criteria for observability-related features.

- Identify opportunities to enhance the data observability landscape including automation metadata capture dashboards and alert maturity.

- Stay current on Bigeye product updates and champion new capabilities across teams.