Note: The job is a remote job and is open to candidates in USA. Frontline Education is on a mission to transform how schools operate, ensuring success for educators and students. They are looking for Senior Software Engineers to join their Data Platform Engineering team, where the role involves designing and building cloud-native data capabilities that support analytics, reporting, and future AI-enabled experiences.
Responsibilities
- Design, build, test, deploy, and support cloud-native data platform capabilities and shared platform services
- Develop scalable ingestion, transformation, orchestration, and data access solutions that support operational and analytical workloads
- Build reusable and discoverable data products that enable reporting, analytics, and business decision-making across Frontline
- Design and support distributed data workflows leveraging event-driven architectures and messaging technologies such as Kafka
- Contribute to data modeling and persistence strategies across relational, analytical, event-oriented, and semi-structured data systems
- Support modernization initiatives that improve scalability, interoperability, governance, and maintainability across the data ecosystem
- Contribute to observability, resiliency, monitoring, troubleshooting, governance enablement, and operational excellence efforts
- Partner with product engineering, reporting, and analytics teams to improve adoption experiences and reduce integration complexity
- Help establish trusted and scalable data foundations that support reporting, analytics, operational insights, and future AI-enabled capabilities
- Collaborate with analytics, reporting, and application teams to support self-service analytics, operational reporting, and interoperable data access patterns
- Design solutions that improve data accessibility, discoverability, quality, governance, and operational readiness
- Contribute to evolving AI-related platform requirements, including feature preparation, retrieval patterns, operational data access, and scalable data consumption
- Help teams make pragmatic decisions that balance traditional analytics approaches with emerging AI opportunities
- Participate in discovery, refinement, and design discussions to evaluate requirements, identify tradeoffs, and shape practical platform solutions
- Collaborate closely with Product Managers, QA Engineers, Architects, Technical Leads, analytics teams, and Engineering Managers throughout the development lifecycle
- Contribute to architectural discussions while aligning solutions to platform standards, governance expectations, and long-term engineering objectives
- Communicate technical concepts, implementation approaches, operational considerations, and platform adoption strategies effectively to both technical and non-technical audiences
- Build strong partnerships across geographically distributed and cross-functional teams
- Develop secure, scalable, maintainable, and high-performing platform solutions
- Contribute to automated testing strategies including unit, integration, operational, and data validation testing
- Participate in code reviews and provide thoughtful technical feedback that improves engineering quality and consistency
- Support CI/CD automation and continuous delivery practices
- Contribute to improvements in observability, governance, resiliency, interoperability, scalability, and developer productivity
- Promote reusable engineering approaches, platform consistency, and sustainable development practices
- Mentor fellow engineers and contribute to a culture of ownership, collaboration, and continuous learning
- Leverage modern AI-assisted development tools such as GitHub Copilot, Claude Code, OpenAI Codex, and emerging technologies to accelerate development, testing, troubleshooting, documentation, and solution exploration
- Apply strong engineering judgment when evaluating and validating AI-generated outputs
- Use AI to improve productivity while maintaining high standards for governance, security, maintainability, scalability, and operational integrity
- Champion responsible and effective AI adoption across engineering workflows
Skills
- Bachelor's degree in Computer Science or a related field, or equivalent professional experience
- 5+ years of professional software engineering, platform engineering, or data platform engineering experience
- Experience designing and building cloud-native data platform capabilities
- Strong understanding of data ingestion, transformation, orchestration, and integration patterns
- Experience working with event-driven architectures, distributed systems, and modern data platforms
- Ability to independently design and deliver complex platform capabilities with high levels of quality, reliability, and maintainability
- Experience participating in technical design discussions and evaluating implementation tradeoffs
- Strong understanding of testing, scalability, governance, interoperability, and operational excellence
- Experience mentoring engineers and contributing to engineering best practices
- Experience leveraging AI-assisted development tools to improve engineering productivity while applying sound judgment and validation practices
- Experience designing and building cloud-native data platform capabilities
- Strong understanding of: Data ingestion and transformation patterns, Event-driven architectures, Distributed data systems, Data interoperability and integration patterns, Analytical and operational data workloads
- Experience with AWS cloud-native services including: S3, Lambda, EC2, SNS/SQS, Container-based workloads, Data and analytics services
- Experience with: Kafka or equivalent messaging technologies, Relational and analytical data systems, Distributed data processing concepts, Docker, CI/CD pipelines
- Familiarity with modern data platform approaches including reusable data products, self-service platform capabilities, and data mesh concepts
- Experience working within Agile software development environments
- Strong communication, collaboration, and problem-solving skills
- Experience with Snowflake, Databricks, Redshift, or similar analytical platform technologies
- Experience with analytics enablement platforms and reporting ecosystems
- Experience building shared platform capabilities consumed across multiple product teams
- Experience supporting AI or machine learning enablement through scalable data platform design
- Familiarity with governance concepts including lineage, discoverability, access control, metadata management, and data quality
- Experience with distributed streaming or CDC-based architectures
- Familiarity with Kubernetes or container orchestration platforms
- Experience working within multi-tenant SaaS environments
- Experience collaborating with geographically distributed engineering teams
- Experience leveraging AI-assisted or agentic development workflows in professional software engineering environments
Benefits
- Personalized Time Off: Take time when it’s needed most — whether that’s a family vacation, a reset day, or simply time to rest and refocus.
- Paid Sick Time: Separate, dedicated sick leave to care for yourself or loved ones.
- Volunteer Time Off: Paid time to give back and support causes that matter to you.
- Ten Paid Holidays: Enjoy meaningful moments and traditions throughout the year.
- World-Class Learning Access: Explore thousands of on-demand courses through platforms like LinkedIn Learning.
- Leadership & Technical Skill Building: Develop new capabilities and chart your own professional path.
- AI Empowerment: Use OpenAI tools to build fluency with emerging technology and harness AI as a creative partner for innovation and problem-solving.
- Tuition Reimbursement: Invest in formal education to advance your skills and career.
- Ongoing Learning Culture: Participate in company-led webinars on AI, inclusion, and industry trends—designed to inspire curiosity and continuous improvement.
- Wellness Initiatives: Company-sponsored programs that support physical, mental, and emotional well-being.
- Employee Assistance Program (EAP): Confidential support for you and your family’s needs.
- Comprehensive Benefits: Health and financial benefits that support your happiness and future.
- Competitive base salary aligned to level, experience, skills, and market data.
- Annual bonus opportunity.
- 401(k) with company match.
- Comprehensive medical, dental, and vision coverage.
- Employee stock purchase opportunities where applicable.
- Tuition reimbursement and professional development support.
- Flexible time off and wellness-focused benefits.
Company Overview
Frontline Education is an integrated insights software primarily focusing on human capital management. It was founded in 1998, and is headquartered in Malvern, Pennsylvania, USA, with a workforce of 501-1000 employees. Its website is http://www.frontlineeducation.com/.Company H1B Sponsorship
Frontline Education has a track record of offering H1B sponsorships, with 3 in 2023, 1 in 2021, 1 in 2020. Please note that this does not guarantee sponsorship for this specific role.