Data Platform Lead
Advantage Tech, Inc.
Kansas City, MO, United States
3 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Compensation
$140,000
Working hours
Regular working hours
Job source
Tech stack
Application Programming Interfaces (APIs)
Computing Platforms
Audit Trail
Automation of Tests
Business Software
Code Review
Information Systems
Computer Programming
Databases
Continuous Integration
Data as a Services
Information Engineering
+20 more
Data Governance
Data Infrastructure
Extract Transform Load (ETL)
Data Warehousing
Distributed Computing Environment
Python (Programming Language)
Operational Databases
Release Management
Secure Coding
Software Engineering
Workflow Management Systems
Enterprise Data Management
Cloud Platform System
Sql Optimization
Technical Debt
Data Lakes
Infrastructure Automation Frameworks
Information Technology
Software Version Control
Data Pipelines
Job description
- Platform architecture: Lead technical design and evolution of enterprise data platform capabilities, including ingestion, storage, transformation, orchestration, and consumption; document architecture decisions and trade-offs.
- Data engineering: Design, build, test, and maintain batch and, where needed, streaming pipelines that integrate data from business applications, databases, APIs, and external sources.
- Data modeling: Develop reusable data models and curated datasets in partnership with analytics teams and data owners; establish clear definitions, lineage, and documentation.
- Reliability and operations: Implement monitoring, alerting, observability, and recovery processes; troubleshoot production issues, lead root-cause analysis, and reduce recurring failures.
- Engineering standards: Establish and reinforce standards for source control, code review, automated testing, CI/CD, infrastructure as code, release management, and technical documentation.
- Security and governance: Partner with security, compliance, and data governance stakeholders to implement access controls, encryption, auditability, retention requirements, and appropriate handling of sensitive data.
- Data quality: Build validation, reconciliation, and exception-handling controls; coordinate resolution of quality issues with source-system owners and business stakeholders.
- Performance and cost: Optimize queries, workloads, storage, and compute utilization; monitor platform spending and recommend improvements that balance cost, scalability, and service requirements.
- Technical leadership: Guide design reviews, mentor engineers, remove technical obstacles, and promote maintainable solutions without creating unnecessary complexity.
- Delivery and partnership: Translate business needs into technical requirements, estimates, and implementation plans; communicate priorities, dependencies, risks, and progress.
- Platform roadmap: Evaluate tools and integration patterns, address technical debt, and recommend practical modernization priorities aligned with business objectives.
- Operational readiness: Maintain runbooks and support documentation; participate in planned maintenance and production support coverage as defined for the role.
Requirements
- Bachelorβs degree in computer science, information systems, engineering, or a related field, or an equivalent combination of relevant education and practical experience.
- Typically seven or more years of relevant data engineering, platform engineering, or related software engineering experience, including experience leading technical initiatives.
- Advanced SQL proficiency and strong programming skills in Python or a comparable language used for data engineering.
- Demonstrated experience designing and operating production data pipelines and enterprise data warehouse, data lake, or lakehouse solutions.
- Hands-on experience with a major cloud platform and its data services, or comparable enterprise-scale data infrastructure.
- Strong understanding of data modeling, ETL/ELT, workflow orchestration, integration patterns, and distributed processing concepts.
- Experience implementing automated testing, version control, CI/CD, monitoring, and secure development practices.
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