Staff Data Engineer

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Dayforce

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

👥 HR Tech

☁️ SaaS

🏢 Enterprise

💰 $1G Post-IPO Debt - Dayforce on 2024-03

HR Tech • SaaS • Enterprise

Dayforce is a cloud-based human capital management (HCM) platform that provides payroll, HR, benefits, workforce management, talent management, and scheduling capabilities in a single application. It is designed for employers to manage the entire employee lifecycle — from hiring and onboarding to payroll and performance — using integrated, real-time data. Dayforce is delivered as a software-as-a-service solution targeted at organizations and HR teams.

📋 Description

• Data is the foundation every AI system at Purpose is built on. This role owns that foundation. • You will join a high-output engineering team and operate at the senior end of that bar, owning the pipelines, data models, and platform infrastructure that data scientists, analysts, AI systems, and downstream products depend on for decisions that move real money and shape real client outcomes. • You'll work closely with data scientists, software engineers, and product teams to understand what data is needed, where it lives, and how to make it accurate, observable, and durable at scale, including the data pipelines that feed our AI systems and the models our advisors and clients will rely on. • You review, tune, and govern AI-assisted development tools that generate initial pipeline structures, dbt model skeletons, and transformation logic from natural language prompts. • You own the standards for first-pass data quality rules and enrich and validate the AI-generated documentation.

🎯 Requirements

• Deep fluency in SQL and Python, designing and maintaining complex transformation logic at scale, with production-grade testing and documentation standards. • Hands-on experience building and operating production data pipelines using modern tooling: dbt, Airflow or equivalent orchestration, and at least one cloud data warehouse (Snowflake, BigQuery, or Redshift). • Strong data modeling foundations - dimensional modeling, slowly changing dimensions, schema design that balances flexibility with query performance. • Meaningful experience in a regulated industry (financial services, healthcare, or equivalent) — you understand what SOC 2 or ISO 27001 compliance means for how pipelines are built, accessed, audited, and controlled. • Experience governing or reviewing AI-assisted code in a production data environment - you've thought carefully about what makes AI-generated pipeline logic safe to deploy. • Familiarity with ML operationalization - feature pipeline design, serving infrastructure, and monitoring for deployed models. • Exposure to LLM data infrastructure: RAG pipelines, vector stores, or embedding workflows. Not required - but this is where the role is heading. • Strong opinions about data contracts and how to formalize interfaces between upstream systems and the data platform. • A track record of raising the data quality bar on an existing team, not just building from a blank page, but inheriting a system and improving its reliability and trustworthiness. • You’ve used AI-assisted development tools (GitHub Copilot, Cursor, Claude Code, or equivalent) as a genuine productivity multiplier, not just experimented with them.

🏖️ Benefits

• Competitive compensation including equity program. • Comprehensive group health and dental benefits and life insurance at little to no cost to you. • Lifestyle Spending Account for all your wellness needs. • A flexible paid time-off policy covering vacation, sick, and mental health days. • Paid parental leave for eligible employees with a top-up. • Generous Group RRSP matching and an optional TFSA program. • Training opportunities and tuition support year-round.