Data Platform Infrastructure Manager

About SailPoint

SailPoint is the leader in identity security for the cloud enterprise. Our identity security solutions secure and enable thousands of companies worldwide giving our customers unmatched visibility into the entirety of their digital workforce and ensuring workers have the right access to do their jobsno more no less.

Built on a foundation of AI and machine learning SailPoint Identity Security delivers the right level of access to the right identities and resources at the right timematching the scale velocity and changing needs of todays cloud-oriented modern enterprise.

About the role

As the Data Infrastructure Platform Manager you will lead the team responsible for the runtime and platform layer beneath SailPoints batch streaming analytics and machine learning workloads. Your team owns the availability scalability security performance lifecycle and cost efficiency of shared services such as Airflow Flink Spark on AWS EMR Kafka Snowflake and Iceberg. Data and product engineering teams own the workload-specific pipelines and processing logic that run on those services.

Your day will span people leadership production operations technical strategy and cross-functional execution. You will review service health and incidents set priorities across operational and roadmap work coach and unblock engineers make architectural and investment tradeoffs and partner with data engineering Developer Platform SRE Observability Security and Infrastructure teams. You will make the platform easier to consume through paved roads CI/CD configuration as code observability automation and self-serviceall while protecting reliability quality and cost efficiency in a fast-moving environment.

About the team

The Data Infrastructure Platform team designs builds and operates the production-grade data processing infrastructure that powers SailPoint Identity Security. We provide reliable scalable and secure data platforms as services so data and product engineers can focus on DAGs streaming jobs pipelines models and business logic rather than provisioning and operating the underlying infrastructure. The team values engineering and operations excellence service ownership practical automation constructive debate continuous learning and a strong opinions loosely held mindset.

Roadmap for success

Success in this role will be measured through the following outcomes:

30 days

• Build working relationships with team members and key partners across data and product engineering Data Operations Developer Platform SRE Observability Security and Infrastructure.
• Document and align stakeholders on the team charter service catalog ownership boundaries escalation paths and the distinction between platform ownership and workload-specific pipeline ownership.
• Complete an initial assessment of the teams people platforms roadmap on-call load incidents operational risks capacity and cloud costs; share a prioritized set of immediate risks and opportunities.
• Establish a regular operating cadence for team priorities service health incidents roadmap delivery and cross-team dependencies.
  

90 days

• Publish an outcome-oriented 12-month platform roadmap developed with technical leads and partner teams that balances reliability scalability security developer experience and cost.
• Define the operating model for the teams highest-criticality services including named ownership service-level objectives observability expectations on-call practices capacity planning lifecycle management and incident follow-up.
• Select and begin delivery of the first high-value paved-road or self-service improvement for deploying and operating Airflow DAGs Flink or Spark jobs or another priority data workload.
• Set clear performance expectations and development goals for each team member identify capability or staffing gaps and establish a hiring and development plan where needed.
• Baseline the platforms key reliability delivery toil utilization and cost measures so subsequent improvements can be demonstrated with data.
  

6 months

• Have service-level objectives actionable dashboards alerts and recurring service reviews in place for the highest-criticality data platform services with measurable progress against the 90-day reliability baseline.
• Deliver at least one production self-service or standardized delivery capability that reduces the effort and lead time required for developers to deploy data workloads safely across supported environments.
• Implement a cost and capacity management program with service-level visibility accountable owners prioritized optimization work and documented efficiency gains.
• Strengthen incident response change management disaster recovery vulnerability remediation and operational runbooks; demonstrate reduced recurring toil or faster recovery for priority failure modes.
• Establish a clear platform approach for supporting machine learning workloads including appropriate use of AWS SageMaker or equivalent capabilities model lifecycle needs and operational guardrails.
  

1 year

• Operate the data infrastructure platform as a mature internal product with a clear service catalog documented support model paved roads self-service capabilities standardized CI/CD and transparent reliability and cost reporting.
• Deliver the highest-priority roadmap outcomes and demonstrate measurable year-over-year improvement in platform availability incident recovery deployment lead time developer effort operational toil and cost efficiency.
• Build a healthy high-performing team with clear ownership strong technical leadership meaningful career growth effective succession coverage and the capability to execute both roadmap and operational work predictably.
• Establish a durable multi-year strategy for Airflow Flink Spark and AWS EMR Kafka Snowflake Iceberg and ML infrastructure that anticipates growth regional expansion security requirements and evolving developer needs.
• Be recognized by partner teams as a responsive reliable platform organization that enables them to deliver data products and business value faster without assuming the burden of operating shared infrastructure.
  

Requirements

• Bachelors degree in Computer Science Engineering or a related field or equivalent professional experience.
• Proven experience managing and leading a cloud infrastructure platform engineering SRE or data infrastructure team responsible for business-critical production services.
• Deep understanding of cloud infrastructure distributed systems and production operations including:
  • 5 years of production experience with AWS.
  • 3 years of experience with Kubernetes and containerized workloads.
  • Ability to read review and troubleshoot software written in Python Go Java or a comparable language.
  • Experience with infrastructure as code preferably Terraform and modern CI/CD or GitOps practices.
  • Strong systems networking security and distributed-systems troubleshooting fundamentals.
• Substantial hands-on experience operating production data platforms at scale with depth in several of the following: Apache Airflow Apache Kafka Apache Flink Apache Spark AWS EMR Snowflake and Apache Iceberg. Experience operating these technologies as shared servicesnot only consuming themis strongly preferred.
• Experience with machine learning systems and their operational lifecycle including practical experience training evaluating or deploying ML models and familiarity with AWS SageMaker or an equivalent ML platform. Databricks experience is a plus.
• Working knowledge of modern LLM capabilities and AI-assisted engineering practices with sound judgment about responsible use validation and production guardrails.
• Demonstrated success building internal platforms as products including self-service developer experiences standardized delivery workflows CI/CD observability and clear service ownership.
• Strong production-operations discipline including metrics and observability SLOs incident response capacity planning disaster recovery and continuous reliability improvement.
• Experience managing cloud infrastructure cost capacity and performance with a track record of making measurable efficiency improvements.
• Excellent leadership communication negotiation and cross-functional collaboration skills including the ability to align teams with competing goals and clarify ambiguous ownership.
• Ability to thrive in a fast-paced environment with shifting priorities and incomplete information while preserving engineering rigor production uptime and quality.
• Experience with Agile or similar iterative planning and delivery practices applied pragmatically to a team that balances roadmap work with operational demand.
• Passion for engineering excellence reliability continuous learning and developing people.
  

The Tech Stack

• Cloud and infrastructure: AWS Amazon EKS Kubernetes Terraform and configuration as code.
• Data orchestration and processing: Apache Airflow Apache Flink Apache Spark and AWS EMR.
• Streaming storage and analytics: Apache Kafka Snowflake Apache Iceberg and AWS data services.
• Delivery and operations: CI/CD GitOps metrics logs traces alerting SLOs and incident management.
• Software: Python Go Java or comparable languages.
• AI and machine learning: AWS SageMaker or equivalent ML platforms modern LLM capabilities and AI-assisted engineering tools. Databricks experience is a plus.
  

SailPoint is an equal opportunity employer and we welcome everyone to our team. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin disability or veteran status.

Benefits and Compensation listed vary based on the location of your employment and the nature of your employment with SailPoint.

As a part of the total compensation package this role may be eligible for the SailPoint Corporate Bonus Plan or a role-specific commission along with potential eligibility for equity participation. SailPoint maintains broad salary ranges for its roles to account for variations in knowledge skills experience market conditions and locations as well as reflect SailPoints differing products industries and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity. We estimate the base salary for US-based employees will be in this range from (min-max USD):

Base salaries for employees based in other locations are competitive for the employees home location.

Benefits Overview

1. Health and wellness coverage: Medical dental and vision insurance

2. Disability coverage: Short-term and long-term disability

3. Life protection: Life insurance and Accidental Death & Dismemberment (AD&D)

4. Additional life coverage options: Supplemental life insurance for employees spouses and children

5. Flexible spending accounts for health care and dependent care; limited purpose flexible spending account

6. Financial security: 401(k) Savings and Investment Plan with company matching

7. Time off benefits: Flexible vacation policy

8. Holidays: 8 paid holidays annually

9. Sick leave

10. Parental support: Paid parental leave

11. Employee Assistance Program (EAP) and Care Counselors

12. Voluntary benefits: Legal Assistance Critical Illness Accident Hospital Indemnity and Pet Insurance options

13. Health Savings Account (HSA) with employer contribution

SailPoint is an equal opportunity employer and we welcome all qualified candidates to apply to join our team. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin disability protected veteran status or any other category protected by applicable law.

Alternative methods of applying for employment are available to individuals unable to submit an application through this site because of a disability. Contact or mail to 11120 Four Points Dr Suite 100 Austin TX 78726 to discuss reasonable accommodations. NOTE: Any unsolicited resumes sent by candidates or agencies to this email will not be considered for current openings at SailPoint.