Senior Engineer, HR Data Analytics

We are a collaborative team of data storytellers, engineers, and analysts who own the end-to-end data lifecycle. Collectively, our expertise spans:

● Global Insights & Reporting: Empowering regional and global stakeholders with accurate, scalable, and on-demand self-service reporting.

● Advanced Analytics: Moving beyond simple metrics to deliver descriptive and inferential statistics, predictive modeling, and time-series analyses that forecast workforce trends.

● Data Visualization: Transforming complex data structures into intuitive, high-impact dashboards that drive executive decision-making.

● Data Governance & Security: Championing HR Master Data Management (MDM) to ensure the highest standards of data integrity, compliance, and security.

● Continuous Innovation: Keeping our pulse on the market to evaluate and adopt cutting-edge analytics tools and emerging methodologies.

About the role:

As the Senior Analytics Engineer, you will serve as the strategic architect of our data ecosystem. You won’t just build data models; you will design the foundational framework that enables advanced analytics, machine learning, and AI capabilities across the organization. This role requires a blend of deep technical mastery in data modeling, strategic foresight, and the ability to bridge the gap between raw data engineering and cutting-edge AI initiatives.

Key Responsibilities:

● Strategic Architecture: Design, scale, and optimize the core HR data warehouse architecture to support enterprise-wide business intelligence, workforce analytics, AI, and machine learning workloads.

● AI & ML Enablement: Partner with Data Science, AI, and HR technology teams to prepare clean training datasets, feature-ready data models, and governed pipelines that support predictive models, LLM applications, and chatbot-based analytics use cases.

● Advanced Data Modeling: Define and implement robust, reusable, and privacy-aware data models using engineering best practices, including version control, CI/CD, automated testing, documentation, and code review.

● Governance, Security & Privacy: Establish frameworks for data governance, quality metrics, lineage, access controls, auditability, and security compliance across all analytics layers, with a strong focus on sensitive HR and employee data.

● Sensitive Data Protection: Design analytics solutions that protect PII and sensitive employee attributes through encryption, masking, tokenization, pseudonymization, row-level security, column-level security, and controlled aggregation.

● Dashboarding & Data Products: Build and support trusted dashboards, curated datasets, and self-service analytics products for HR and business stakeholders, preferably using Tableau or similar visualization platforms.

● Mentorship & Leadership: Act as a technical mentor to junior engineers, championing high standards for code quality, documentation, data modeling, system design, and secure development practices.

Qualifications:

● 5+ years of experience in Analytics Engineering, Data Engineering, Business Intelligence Engineering, or a similar role, preferably in People Analytics, HR data, or another sensitive data environment.

● Expert-level proficiency with modern cloud data warehouses such as Google BigQuery, Snowflake, or similar platforms, with advanced SQL and strong data modeling skills.

● Hands-on experience with dbt, git workflows, automated testing, and data orchestration tools such as Airflow, Prefect, or Dagster.

● Strong understanding of data security principles, including encryption at rest and in transit, cloud KMS, IAM, service accounts, secrets management, key rotation, and secure data-sharing patterns.

● Experience working with PII or sensitive employee data, including practical knowledge of masking, tokenization, pseudonymization, row-level security, column-level security, or controlled aggregation.

● Working knowledge of CI/CD practices, deployment workflows, environment management, and containers such as Docker.

● Exposure to AI/ML, LLM, or chatbot-related data use cases, with Python proficiency highly preferred.

● Experience building dashboards, reports, and self-service analytics products for business users, preferably using Tableau or similar BI tools.

● Deep understanding of HR functions and how data structures, systems, definitions, and processes differ across domains such as workforce, recruiting, compensation, benefits, performance, employee relations, learning, and talent management.

● Experience working with contemporary HR technology platforms is preferred, such as Workday, ServiceNow, or similar enterprise systems.

● Ability to plan and execute complex projects, prioritize competing demands across individual and team responsibilities, and communicate effectively with cross-functional business and technical stakeholders.

● Strong systems thinking and the ability to influence stakeholders while maintaining high standards for data quality, security, documentation, and governance.

Good to Have:

● Experience with semantic layer or metrics layer tools such as dbt Semantic Layer, Cube, or MetricFlow to standardize business definitions and enable consistent self-service analytics.