DataOps Engineer

## About the Role As a DataOps Engineer at Greystar, you will be responsible for managing and operating the company's enterprise data infrastructure, which is built on a Databricks-native medallion architecture and runs entirely on Microsoft Azure. This is a highly technical, hands-on role that requires a deep understanding of Databricks, Azure, and AI-driven observability. You will be part of the Data Marketplace team and will work closely with other engineers and stakeholders to ensure the reliability, scalability, and operational excellence of the platform. The DataOps Engineer role is critical to Greystar's success, as it enables the company to make data-driven decisions and drive business growth. You will be working on a wide range of tasks, from designing and implementing data pipelines to monitoring and optimizing platform performance. Your expertise in Databricks, Azure, and AI-driven observability will be essential in ensuring that the platform is running smoothly and efficiently. Greystar is a leading global real estate platform, and its Data Marketplace team is at the forefront of the company's data-driven initiatives. As a DataOps Engineer, you will be part of a dynamic team that is passionate about innovation and excellence. You will have the opportunity to work with cutting-edge technologies and collaborate with other experts in the field. ## What You Will Do - Implement AI-powered observability using LLMs and ML models to detect pipeline drift, classify anomalies, and predict SLA risk - Design and maintain ADF pipelines for source system ingestion, including orchestration patterns for multi-tenant ERP environments - Collaborate with Azure infrastructure and cloud engineering teams on networking, identity, security, and resource provisioning - Develop and maintain AI-assisted root cause analysis tooling to reduce MTTR on pipeline failures - Own the full deployment lifecycle, promoting data pipeline changes and platform configurations across dev, staging, and production environments - Operate the full Azure data services stack supporting DMP, including ADLS Gen2, Azure Data Factory, Azure Monitor, Log Analytics, Key Vault, and Event Hub - Build agentic monitoring workflows that proactively surface data quality degradation, pipeline dropout, schema drift, and volume anomalies - Integrate AI tooling into operational DataOps processes, including Databricks Mosaic AI, Genie, OpenAI APIs, or equivalent - Contribute to Greystar's 18-month agentic AI roadmap, leading near-term delivery of self-healing pipeline capabilities - Drive the adoption of CI/CD discipline, environment promotion hygiene, and release coordination across the team ## What We Are Looking For - 5+ years of experience in a similar role, with a strong background in data engineering and operations - Expertise in Databricks, Azure, and AI-driven observability, including LLMs and ML models - Strong understanding of data pipelines, data quality, and data governance - Experience with Azure data services, including ADLS Gen2, Azure Data Factory, Azure Monitor, and Key Vault - Strong programming skills in languages such as Python, Scala, or Java - Experience with CI/CD tools such as GitHub Enterprise and Linear - Strong communication and collaboration skills, with the ability to work with cross-functional teams - Bachelor's degree in Computer Science, Engineering, or a related field ## Nice to Have - Experience with cloud-based data services, including AWS or Google Cloud - Knowledge of data science and machine learning concepts, including data modeling and predictive analytics - Experience with agile development methodologies and DevOps practices - Certification in Azure, Databricks, or related technologies ## Benefits and Perks - Competitive salary and benefits package - Opportunity to work with cutting-edge technologies and collaborate with other experts in the field - Flexible working hours and remote work options - Professional development and training opportunities - Access to a comprehensive health and wellness program - Generous paid time off and holiday package - 401(k) matching and retirement savings plan

- Tip: Make sure to highlight your experience with Databricks, Azure, and AI-driven observability in your resume and cover letter.

• Tip: Be prepared to discuss your approach to data pipeline design, implementation, and optimization during the interview.
• Tip: Showcase your understanding of data governance and quality, and how you ensure data integrity and compliance.
• Tip: Emphasize your experience with CI/CD tools and agile development methodologies.
• Tip: Research Greystar's company culture and values, and be prepared to discuss how you align with them.
• Tip: Prepare to back up your claims with specific examples from your experience, and be ready to answer behavioral questions.
• Tip: Don't be afraid to ask questions during the interview, such as what the team's dynamics are like or what opportunities there are for growth and development.