Senior Platform Engineer

Specialty Software Engineering Consultant

In this contingent resource assignment, you may:

• Consult on complex initiatives with broad impact and large-scale planning for Specialty Software Engineering.
• Review and analyze complex multi-faceted, larger scale, or longer-term Specialty Software Engineering challenges that require in-depth evaluation of multiple factors, including intangibles or unprecedented factors.
• Contribute to the resolution of complex and multi-faceted situations requiring solid understanding of the function, policies, procedures, and compliance requirements that meet deliverables.
• Strategically collaborate and consult with client personnel.

Required Qualifications:

• 5+ years of Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.
• We are seeking a mid-level to senior engineer to join our team on a contract basis to help design, build, and operate a secure, scalable enterprise Data Private Cloud (DPC) platform.
• This is a hybrid role that blends container-platform development (Kubernetes/OpenShift and data services) with security operations (SecOps) and automation.
• You will build and enhance platform services and workflows across the SDLC, implement security controls and compliance guardrails, and partner with cross-functional teams to operationalize secure-by-default data services at scale.

Platform Engineering:

• Design and build automated platform workflows for provisioning, deployment, and operational support of data services running on OpenShift/Kubernetes.
• Develop and maintain platform capabilities supporting data ecosystem components such as Spark, Iceberg, Ranger, Sparkflow, Superset, and related services.
• Contribute to resilient, scalable architecture for containerized workloads and large-scale data processing pipelines.
• Improve platform reliability through automation, runbooks, SRE practices, and standard operating procedures.

Security Engineering & SecOps Enablement:

• Engineer security automation that enforces controls for data access, encryption, masking, and protection across the data platform.
• Integrate security into the SDLC by embedding controls into CI/CD pipelines, infrastructure-as-code, and release processes.
• Support security monitoring and compliance by contributing to:
• Policy management, attestation evidence, and continuous compliance workflows
• Security-relevant audit logging, alerting, and dashboards
• Partner with security, platform, and DevOps teams to strengthen incident response readiness, operational resilience, and risk reduction.

Hands-on Development & Collaboration:

• Design, implement, test, and document Python-based services and automation for platform operations and compliance workflows.
• Collaborate closely with architects, DevOps/platform engineers, and data product teams to deliver end-to-end solutions.
• Participate in technical design reviews, threat modelling discussions, and architecture decisions for secure deployment patterns.

Required Qualifications (5+ years) Core Skills:

Strong Python development skills for enterprise-scale automation and service development. Solid understanding of security fundamentals (least privilege, defense-in-depth, secure SDLC) and common compliance concepts. Experience building or operating software in containerized environments (Kubernetes or OpenShift/OCP). Practical experience with CI/CD pipelines and integrating security checks/controls into delivery workflows. Strong communication skills and ability to work effectively across engineering and security stakeholders.

Technical Background:

Familiarity with data security patterns such as access control, encryption, tokenization/masking, and secrets management. Understanding of DevOps practices: automated testing, release automation, environment promotion strategies, and operational support. Exposure to data platform concepts (data services, governance, metadata, batch/stream processing).

Preferred Qualifications (Nice to Have):

Experience with Apache/open-source ecosystem tools such as Ranger, Keycloak, Spark, Iceberg, DataHub. Knowledge of S3-compatible object storage and large-scale distributed data processing patterns. Familiarity with observability tooling (logs/metrics/traces), security telemetry, and operational health dashboards. Experience with incident response, post-incident reviews, and improving operational resilience. Exposure to API design and/or UI development (e.g., React.js) for operational portals or admin tools.

What Success Looks Like:

Automated workflows that make data services easy to deploy and operate on OCP/Kubernetes. Security controls that are built-in, not bolted-on—policy enforcement, least privilege, auditability, and compliance automation. Improved reliability and reduced operational overhead through standardization and automation. Strong cross-team alignment between platform engineering, data teams, and security stakeholders.

EEO:

"Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans."