Data Platform Engineer

Artisan Partners
Milwaukee, WI, United States
3 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Databases Continuous Integration Data as a Services Data Infrastructure Data Integrity Data Systems Data Warehousing Relational Databases Database Queries Digital Architecture Disaster Recovery
+21 more
Distributed Systems Python (Programming Language) PostgreSQL Meta-Data Management Microsoft SQL Server Online Analytical Processing Online Transaction Processing Operational Databases Cloud Services DataOps SQL Server Analysis Services Enterprise Data Management Data Logging Scripting System Availability Snowflake Data Lakes Infrastructure Automation Frameworks Deployment Automation Software Version Control Programming Languages

Job description

Artisan Partners is seeking a Data Platform Engineer to join our Data Platform Systems team. This team is responsible for the infrastructure, services, security controls, and engineering and operational practices that support firm-wide data availability, reliability, integrity, and compliance.

In this role, you will help design, build, operate, and improve the platforms that enable secure and dependable access to enterprise data. You will work closely with data engineers, application teams, infrastructure teams, compliance partners, and business stakeholders to ensure critical data services are scalable, well-governed, resilient, and supportable., The candidate is expected to:

  • Design, implement, and support the platforms that underpin firm-wide data systems, from databases to orchestration to cloud services.
  • Maintain and improve platform availability, performance, security, integrity, usage, and reliability
  • Automate deployment, configuration, monitoring, alerting, validation, and operational workflows
  • Support data integrity, control, reconciliation, lineage, and auditability initiatives
  • Troubleshoot production issues, perform root cause analysis, and implement durable fixes
  • Improve observability through metrics, logging, alerting, and service health reporting
  • Contribute to data operations efforts, including change management, infrastructure as code, audit/metadata management, and cloud provider usage
  • Document architecture, operational procedures, support models, and technical standards
  • Support incident response, on-call rotation, change management, disaster recovery, and business continuity planning
  • Apply AI thoughtfully to accelerate work while maintaining the judgment, review, and risk controls the environment demands

Requirements

Do you have experience in Version control?, The successful candidate will possess strong analytical skills and attention to detail. Additionally, the ideal candidate will possess:

  • 3 -5 years of experience engineering, supporting, and operating enterprise data platforms, infrastructure services, or distributed systems
  • Experience with OLTP/OLAP database management systems (SQL Server, PostgreSQL, SQL Server Analysis Services, Snowflake)
  • Experience with enterprise orchestration and general automation best practices
  • Sound judgment and appropriate care when working with production data platforms, including awareness of accuracy, integrity, availability, security, and business impact
  • Strong SQL skills and experience with relational databases, data warehouses, or data lake platforms
  • Experience with Python or similar scripting/programming languages
  • Experience with data operations and change management (CI/CD, source control, infrastructure as code, etc.)
  • Understanding of monitoring, logging, alerting, and production support practices
  • Troubleshooting ability across data, application, infrastructure, and integration layers
  • Familiarity with least-privilege security, access control, and secure administration principles
  • Ability to work in a controlled, compliance-sensitive environment with attention to auditability, documentation, and risk management
  • Comfort using AI tools and platforms to improve productivity, quality, and delivery
  • Strong communication and collaboration skills with technical and non-technical stakeholders

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