data platform engineer

IDEA Public Schools

<div>Description 
 
 
Data Platform Engineer 
 This is a vacancy for the 26-27 school year with a target start date of July 1, 2026
Mission:
The Data Platform Engineer builds and operates IDEA&rsquo;s data infrastructure on Snowflake, enabling reliable, scalable access to data that supports analytics, reporting, and research across multiple states. This role designs automated ingestion pipelines, optimizes platform performance and cost, and ensures the data platform functions as a production-grade system for downstream teams. 
 
Reporting to the Manager of Data Platform Engineering, this engineer works hands-on with ELT pipelines, infrastructure-as-code, and Snowflake administration while contributing to IDEA&rsquo;s transition from legacy ETL systems to a modern lakehouse architecture. 
Supervisory Responsibilities:
Individual contributor role with no direct reports. Senior engineers may mentor peers and lead technical initiatives. 
Location:
This is a full-time remote position based in Texas, with preference given to candidates who live in Austin, El Paso, Houston, Permian Basin (Midland/Odessa), Rio Grande Valley, San Antonio, and Tarrant County (Fort Worth), or who are willing to relocate. 
Travel Expectations:
Minimal travel (5&ndash;10% annually) for collaboration, training, or critical implementation milestones. 
What You&rsquo;ll Do &ndash; Accountabilities
Essential Duties:<ul><li>
Design, build, and maintain automated ELT pipelines ingesting data from diverse source systems into Snowflake.
</li><li>Configure and manage cloud-native ingestion tools and custom Python-based pipelines when needed.</li><li>
Build and maintain Bronze-layer tables with schema evolution handling, audit metadata, and lineage.</li><li>
Implement ingestion-level validation and monitoring to catch issues early.</li><li>
Document source configurations, refresh schedules, and troubleshooting procedures.</li><li>
Partner with Analytics Engineering to ensure ingestion patterns support downstream transformation needs.</li><li>
Administer Snowflake environments, including databases, schemas, warehouses, access controls, and security settings.</li></ul> 
Additional Duties and Responsibilities:<ul><li>
Optimize performance and cost through warehouse sizing, clustering, query analysis, and resource monitoring.</li><li>
Manage Snowflake objects using infrastructure-as-code patterns.</li><li>
Implement security best practices including RBAC, encryption, auditing, and network policies.</li><li>
Evaluate and adopt new Snowflake capabilities as appropriate.</li><li>
Own Terraform-based infrastructure definitions for Snowflake and related platform components.</li><li>
Automate recurring operational tasks such as provisioning, access grants, and environment setup.</li><li>
Build CI/CD pipelines for infrastructure changes with testing and safe deployment practices.</li><li>
Develop reusable templates and modules to accelerate onboarding of new sources and domains.</li><li>
Maintain clear documentation and runbooks for platform operations.</li><li>
Implement monitoring and alerting for pipelines, platform health, and performance.</li><li>
Troubleshoot pipeline failures and platform issues using systematic root-cause analysis.</li><li>
Embed observability (logging, metrics, alerts) into all production pipelines.</li><li>
Collaborate closely with Analytics Engineering, DataOps, and Data Governance partners.</li><li>
Participate in code reviews and design discussions.</li><li>
Share platform knowledge through documentation, mentoring, and team forums.</li><li>
Contribute to retrospectives and continuous improvement efforts.</li></ul> 
Knowledge and Skills &ndash; Competencies<ul><li>
Make Strategic Decisions: This team member uses data, feedback, and insights to inform thoughtful decision-making, while considering the impact on their direct reports and team. They communicate decisions with clear rationale and begin to connect their choices to broader team objectives.
</li><li>Manage Work and Teams: This team member sets clear, measurable goals and regularly reflects on progress, adjusting actions as needed. They prioritize work aligned with their goals using a task management system and consistently meet deadlines through effective time management.</li><li>
Grow Self and Others: This team member regularly offers affirming and adjusting feedback, maintaining a positive balance that reinforces growth and motivation. They provide transparent, candid performance insights and offer consistent coaching and development aligned with individual goals, supporting both direct reports and cross-functional partners.</li><li>
Build a Culture of Trust: This team member proactively builds strong personal and professional relationships with individual stakeholders and regularly seeks feedback to improve their work experience. They create a supportive environment where others feel safe to take risks and learn from mistakes without fear of retribution.</li><li>
Communicate Deliberately: This team member communicates thoughtfully by anticipating potential misunderstandings and providing necessary context to ensure clarity. They leverage structured communication channels to address challenges, ask meaningful questions, and guide conversations toward solutions, while actively listening to the concerns of others.</li></ul> 
Additional Skills:
Required<ul><li>
Hands-on experience administering Snowflake or similar cloud data platforms.</li><li>
Strong SQL skills for data extraction, validation, and performance tuning.</li><li>
Experience building and operating automated data pipelines.</li><li>
Proficiency with Python and scripting for automation and operational tooling.</li><li>
Experience operating production systems with monitoring and incident response.</li><li>
Familiarity with infrastructure-as-code and CI/CD concepts.</li></ul> 
Preferred<ul><li>
Experience with cloud-native ingestion tools (e.g., Fivetran, Airbyte).</li><li>
Experience with Terraform or similar IaC tooling.</li><li>
Familiarity with dbt and analytics engineering workflows.</li><li>
Exposure to orchestration, data quality, or observability tools.</li><li>
Experience with education, public sector, or regulated data environments.</li></ul> 
Required Education and Experience:<ul><li>
Bachelor&rsquo;s degree in a technical field or equivalent practical experience.</li><li>
3+ years of experience in data engineering, platform engineering, or related roles.</li><li>
Demonstrated experience building and operating production data systems.</li><li>
Hands-on experience with Snowflake or comparable cloud data warehouses.</li></ul> 
Preferred Education and Experience:
<ul><li>Snowflake or cloud platform certifications.</li><li>
Experience supporting multi-team data platforms at scale.</li><li>
Strong Python proficiency beyond basic scripting.</li></ul> 
Physical Requirements:<ul><li>
Prolonged periods working on a computer and in virtual meetings</li><li>
Ability to travel domestically via car and air travel to campuses and state office</li><li>
Flexibility for occasional evening meetings with distributed stakeholders across time zones</li></ul> 
What We Offer: 
Compensation &amp; Benefits:
Salaries for people entering this role typically fall between $89,600 and $105,300, commensurate with relevant experience and qualifications and in alignment with internal equity. This role is also eligible for performance pay based on organizational performance and goal attainment. 
Additionally, we offer medical, dental, and vision plans, disability, life insurance, parenting benefits, flexible spending account options, generous vacation time, referral bonuses, professional development, and a 403(b) plan. You can find more information about our benefits at https://ideapublicschools.org/careers/benefits/.<ul><li> 
IDEA may offer a relocation stipend to defray the cost of moving for this role, if applicable.</li></ul> 
Application process:
Submit your application online through Jobvite. Please note that applications will be reviewed on an ongoing basis until the position is filled. Applicants are encouraged to apply as early as possible. 
Learn more about IDEA
At IDEA the Staff Experience Team uses our Core Values to promote human connection and a culture of integrity, respect, and belonging for all Team and Family members. Learn more about our Commitment to Core Values here: https://ideapublicschools.org/our-story/#core-values</div>

Data Platform Engineer (26-27)

RHP Properties

<div>Job Description
Who is RHP Properties?
Headquartered in Farmington Hills, Michigan, RHP Properties (www.rhp.com) is the nation's largest private owner and operator of manufactured home communities. With more than 380 communities throughout 33 states, we continue to expand our footprint to provide accessible and affordable housing across the country. All of this would not be possible without the energy and drive of our talented employees! We invest in our employees, with regular training, opportunities for advancement, and fun events to bring everyone together.
RHP Properties is seeking Data Platform Engineer to lead the design, implementation, and evolution of the company's Microsoft Fabric data platform. This role will play a critical part in modernizing the enterprise data ecosystem by migrating legacy reporting and data systems into a scalable, governed, and high-performance Lakehouse architecture. This position combines data architecture, engineering, and platform ownership, requiring both strategic thinking and hands-on implementation. The successful candidate will design data models, build robust pipelines, integrate enterprise systems, and establish engineering best practices that support reliable analytics across the organization. This role focuses on data platform engineering and architecture rather than report development, ensuring RHP has a strong foundation for analytics, automation, and future AI initiatives.
As RHP transitions toward a modern Fabric-based analytics ecosystem, this role will lead the technical design and implementation of the enterprise data platform. You will work closely with leadership, analysts, and engineering teams to build a trusted enterprise data foundation that enables:<ul><li>
Scalable data pipelines</li><li>
Standardized semantic models</li><li>
Governed self-service analytics</li><li>
High-performance reporting</li><li>
Advanced analytics and AI readiness</li></ul>
The role requires a strong engineering mindset and experience building production-grade data platforms rather than simply developing reports or dashboards.
Key Responsibilities
Platform Architecture &amp; Migration<ul><li>
Design and implement RHP&rsquo;s Microsoft Fabric data architecture including Lakehouse, Warehouse, Pipelines, and Notebooks.</li><li>
Lead migration of legacy data sources including SQL Server, flat files, SharePoint, APIs, and SFTP feeds into the Fabric platform.</li><li>
Implement medallion architecture (Bronze / Silver / Gold) and enterprise data modeling standards.</li><li>
Optimize performance, refresh speed, and scalability of data pipelines and semantic models.</li><li>
Define architectural patterns that support long-term platform scalability.</li></ul>
Data Engineering &amp; Integration<ul><li>
Build robust and scalable data ingestion pipelines using modern ELT/ETL patterns.</li><li>
Develop Python and SQL-based transformation frameworks to support repeatable data workflows.</li><li>
Integrate internal and external systems through APIs, secure data transfers, and automated pipelines.</li><li>
Implement data validation, logging, monitoring, and error handling to ensure reliability.</li><li>
Develop reusable frameworks for data ingestion and transformation.</li></ul>
Analytics Enablement<ul><li>
Design and maintain enterprise semantic models that serve as the trusted layer for reporting.</li><li>
Optimize Power BI datasets and semantic models for performance and usability.</li><li>
Enable self-service analytics by providing structured, governed datasets for analysts and business teams.</li><li>
Partner with analytics teams to improve data accessibility and reduce reporting inefficiencies.</li></ul>
Data Governance &amp; Quality<ul><li>
Implement enterprise data governance standards including naming conventions, lineage tracking, and access controls.</li><li>
Establish automated data quality validation frameworks.</li><li>
Ensure consistency, reliability, and traceability of enterprise data assets.</li><li>
Maintain documentation of data models, transformations, and platform architecture.</li></ul>
Data Platform Reliability<ul><li>
Implement monitoring and observability across pipelines and data models.</li><li>
Establish alerting mechanisms for data failures and performance degradation.</li><li>
Improve reliability and resilience of production data workloads.</li><li>
Identify and resolve bottlenecks in data pipelines and processing layers.</li></ul>
Engineering Practices<ul><li>
Implement Git-based version control for data platform artifacts.</li><li>
Develop CI/CD workflows for deployment and promotion of data pipelines and models.</li><li>
Promote testing, documentation, and maintainable engineering practices.</li><li>
Encourage reusable data engineering patterns and modular pipeline design.</li></ul>
Technology Stack
The data platform environment includes technologies such as:<ul><li>
Microsoft Fabric (Lakehouse, Warehouse, Pipelines, Notebooks)</li><li>
Power BI Semantic Models</li><li>
Python and SQL</li><li>
Azure Storage / Data Lake</li><li>
API integrations</li><li>
Git version control</li><li>
Data pipeline orchestration and monitoring tools</li></ul>
Job Requirements
Required Technical Skills<ul><li>
Experience working with modern cloud data platforms such as Microsoft Fabric, Azure Synapse, Databricks, Snowflake, or similar.</li><li>
Strong Python and advanced SQL skills.</li><li>
Experience designing data warehouses and dimensional data models.</li><li>
Experience building data pipelines and ELT/ETL frameworks.</li><li>
Experience integrating data via APIs and automated data ingestion pipelines.</li><li>
Experience optimizing semantic models and Power BI datasets.</li><li>
Understanding of modern data architecture patterns such as medallion architecture and star schemas.</li></ul>
Professional Attributes
Successful candidates will demonstrate:<ul><li>
Strong ownership mindset and execution discipline</li><li>
Ability to solve complex technical problems</li><li>
Focus on automation and process improvement</li><li>
Curiosity and adaptability with emerging technologies</li><li>
Attention to detail and commitment to high-quality engineering standards</li><li>
Strong communication skills and stakeholder empathy
</li></ul>Qualifications<ul><li>
Experience migrating legacy systems to cloud-based data platforms.</li><li>
Experience implementing CI/CD pipelines and DevOps practices.</li><li>
Experience with Git version control workflows.</li><li>
Experience implementing data governance frameworks.</li><li>
Familiarity with real estate, property management, or operational analytics.</li><li>
Minimum 3&ndash;5 years of hands-on experience delivering production data solutions.</li><li>
Proven track record building scalable data platforms, pipelines, or analytics architectures.</li><li>
Experience working with cross-functional teams to deliver enterprise data initiatives.</li></ul>
Success Indicators (First 6 Months)
A successful hire will:<ul><li>
Establish Foundational Fabric platform architecture</li><li>
Deploy production-grade data pipelines</li><li>
Improve performance and reliability of enterprise datasets</li><li>
Standardize semantic models and reporting logic</li><li>
Reduce manual reporting and data inefficiencies</li><li>
Improve visibility and trust in enterprise data</li></ul>
We are Proud to Provide the following:<ul><li>
Access to benefits including medical, dental and vision insurance</li><li>
401K with company match</li><li>
Short-term and long-term disability</li><li>
Life insurance</li><li>
Generous Paid Time Off and holidays</li><li>
Flexible spending account</li></ul></div>

Data Platform Engineer

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