[Remote] Senior Software Engineer I or II- Data Platform

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.ResponsibilitiesDesign, build, test, deploy, and support cloud-native data platform capabilities and shared platform servicesDevelop scalable ingestion, transformation, orchestration, and data access solutions that support operational and analytical workloadsBuild reusable and discoverable data products that enable reporting, analytics, and business decision-making across FrontlineDesign and support distributed data workflows leveraging event-driven architectures and messaging technologies such as KafkaContribute to data modeling and persistence strategies across relational, analytical, event-oriented, and semi-structured data systemsSupport modernization initiatives that improve scalability, interoperability, governance, and maintainability across the data ecosystemContribute to observability, resiliency, monitoring, troubleshooting, governance enablement, and operational excellence effortsPartner with product engineering, reporting, and analytics teams to improve adoption experiences and reduce integration complexityHelp establish trusted and scalable data foundations that support reporting, analytics, operational insights, and future AI-enabled capabilitiesCollaborate with analytics, reporting, and application teams to support self-service analytics, operational reporting, and interoperable data access patternsDesign solutions that improve data accessibility, discoverability, quality, governance, and operational readinessContribute to evolving AI-related platform requirements, including feature preparation, retrieval patterns, operational data access, and scalable data consumptionHelp teams make pragmatic decisions that balance traditional analytics approaches with emerging AI opportunitiesParticipate in discovery, refinement, and design discussions to evaluate requirements, identify tradeoffs, and shape practical platform solutionsCollaborate closely with Product Managers, QA Engineers, Architects, Technical Leads, analytics teams, and Engineering Managers throughout the development lifecycleContribute to architectural discussions while aligning solutions to platform standards, governance expectations, and long-term engineering objectivesCommunicate technical concepts, implementation approaches, operational considerations, and platform adoption strategies effectively to both technical and non-technical audiencesBuild strong partnerships across geographically distributed and cross-functional teamsDevelop secure, scalable, maintainable, and high-performing platform solutionsContribute to automated testing strategies including unit, integration, operational, and data validation testingParticipate in code reviews and provide thoughtful technical feedback that improves engineering quality and consistencySupport CI/CD automation and continuous delivery practicesContribute to improvements in observability, governance, resiliency, interoperability, scalability, and developer productivityPromote reusable engineering approaches, platform consistency, and sustainable development practicesMentor fellow engineers and contribute to a culture of ownership, collaboration, and continuous learningLeverage modern AI-assisted development tools such as GitHub Copilot, Claude Code, OpenAI Codex, and emerging technologies to accelerate development, testing, troubleshooting, documentation, and solution explorationApply strong engineering judgment when evaluating and validating AI-generated outputsUse AI to improve productivity while maintaining high standards for governance, security, maintainability, scalability, and operational integrityChampion responsible and effective AI adoption across engineering workflowsSkillsBachelor's degree in Computer Science or a related field, or equivalent professional experience5+ years of professional software engineering, platform engineering, or data platform engineering experienceExperience designing and building cloud-native data platform capabilitiesStrong understanding of data ingestion, transformation, orchestration, and integration patternsExperience working with event-driven architectures, distributed systems, and modern data platformsAbility to independently design and deliver complex platform capabilities with high levels of quality, reliability, and maintainabilityExperience participating in technical design discussions and evaluating implementation tradeoffsStrong understanding of testing, scalability, governance, interoperability, and operational excellenceExperience mentoring engineers and contributing to engineering best practicesExperience leveraging AI-assisted development tools to improve engineering productivity while applying sound judgment and validation practicesExperience designing and building cloud-native data platform capabilitiesStrong understanding of: Data ingestion and transformation patterns, Event-driven architectures, Distributed data systems, Data interoperability and integration patterns, Analytical and operational data workloadsExperience with AWS cloud-native services including: S3, Lambda, EC2, SNS/SQS, Container-based workloads, Data and analytics servicesExperience with: Kafka or equivalent messaging technologies, Relational and analytical data systems, Distributed data processing concepts, Docker, CI/CD pipelinesFamiliarity with modern data platform approaches including reusable data products, self-service platform capabilities, and data mesh conceptsExperience working within Agile software development environmentsStrong communication, collaboration, and problem-solving skillsExperience with Snowflake, Databricks, Redshift, or similar analytical platform technologiesExperience with analytics enablement platforms and reporting ecosystemsExperience building shared platform capabilities consumed across multiple product teamsExperience supporting AI or machine learning enablement through scalable data platform designFamiliarity with governance concepts including lineage, discoverability, access control, metadata management, and data qualityExperience with distributed streaming or CDC-based architecturesFamiliarity with Kubernetes or container orchestration platformsExperience working within multi-tenant SaaS environmentsExperience collaborating with geographically distributed engineering teamsExperience leveraging AI-assisted or agentic development workflows in professional software engineering environmentsBenefitsPersonalized 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 OverviewFrontline 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 SponsorshipFrontline 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.