[Remote] Staff Engineer Data

Note: The job is a remote job and is open to candidates in USA. Paylocity is an award-winning provider of cloud-based HR and payroll software solutions. The Staff Data Engineer is responsible for designing and implementing scalable data systems that support enterprise reporting and analytics, while also providing advisory input into organizational architecture decisions.ResponsibilitiesDesign, build, and evolve scalable, secure, and resilient data platform capabilities that support enterprise reporting, analytics, and downstream consumers including BI and ML/AI solutionsDevelop and maintain ELT pipelines, analytical and reporting data models, and curated datasets optimized for reliability, performance, and reuseWrite modular, well-architected, maintainable code designed for reuse across teams (shared libraries, templates, reference implementations)Apply scalability, reliability, and distributed-systems thinking to production data workloads (idempotency, retries, backpressure, failure isolation, recovery)Always think in terms of architecture for your domain and beyond; connect local decisions to platform-wide patterns and downstream consumersFloat between teams to accelerate vague or ambiguous initiatives, reduce duplication, and increase reuse through shared capabilities and standardsProvide advisory input into organizational and system architecture decisions that impact or integrate with the data platformIdentify, advocate for, and complete high-impact coding projects (e.g., refactoring, simplification, platform hardening) that reduce technical debt and increase leverageOwn and be accountable for large project features end-to-end, including design, delivery, rollout, reliability, and cost awarenessOwn health when issues arise or costs spike in areas you’re working around/with; lead triage, drive root-cause analysis, and land preventive fixesProactively identify risks and issues (correctness, reliability, security, cost, delivery); communicate early and mitigate through design and executionDemonstrate attention to quality, performance, and observability by ensuring monitoring, actionable alerts, and practical runbooks for owned areasEstablish, influence, and drive adoption of coding standards, data standards, and operational best practices across the data engineering spaceContribute to and help evolve data governance and operating models that improve data quality, consistency, and trustAdvocate for automation and efficiency across the data engineering workflow (CI/CD, testing, repeatable deployments, documentation, lineage)Identify and solve quality problems in others’ code with actionable review feedback, pairing, and driving follow-through to resolutionMaintain a high bar in code reviews and technical design discussions (clarity, correctness, testing, operability, alignment to standards)Balance technical complexity with user experience and consumer needs (reporting applications, BI consumers, ML/AI use cases)Gain alignment from team-level to org-wide on technical strategy and best practices by influencing through clear proposals, prototypes, and coachingEffectively partner with project stakeholders and leadership to clarify goals, manage tradeoffs, and drive outcomesServe as a formal technical lead on projects; delegate work effectively by providing context and success criteria, fostering growth and ownership throughout the teamFocus on high-priority projects first; explicitly deprioritize lower-value work and communicate tradeoffs clearlyActively mentor or coach all team members, providing feedback to grow hard skills (design, SQL/Python quality) and soft skills (communication, influence)Resolve conflict and foster productive discussions; encourage an open and inclusive cultureDrive continuous team improvement by turning learnings into updated standards, patterns, and practicesDemonstrate significant learning outside of primary team responsibilities and apply it to improve the data platform and team effectivenessSkillsBachelor's degree in Computer Science, Data Engineering, or related discipline or equivalent practical experience7+ years of experience in data engineering, including ownership of large-scale production data systems and hands-on leadership as a technical leadStrong expertise in cloud architectures, distributed systems, and automation, especially within AWS-based data platformsDeep hands-on experience with reporting and analytics data modeling and ELT pipelinesStrong experience with Snowflake, dbt, Python, and SQL with exception-level proficiencyExperience with real-time or event-driven data processing (e.g., Kinesis, EventBridge) and orchestration (e.g., MWAA/Airflow)Experience enabling a broad set of consumers, from reporting applications and BI to ML/AI solutions built on top of curated data productsProven track record optimizing large-scale data platforms for reliability, performance, and costBenefitsMedicalDentalVisionLifeDisability401(k) matchPerks that support you, your family, and your financesCompany OverviewPaylocity is a provider of cloud-based payroll and human capital management (HCM) software solutions. It was founded in 1997, and is headquartered in Schaumburg, Illinois, USA, with a workforce of 5001-10000 employees. Its website is http://www.paylocity.com.