Senior/Principal Analytics Engineer

Job Description

Join our innovative team as an Analytics Engineer and help shape the future of our integrated HR data platform. You’ll play a key role in building robust data transformation pipelines and curated data models that drive self-service analytics and AI initiatives across the organization. As a core member of our data team, you’ll collaborate with product managers, data engineers, and business stakeholders to design and implement a scalable, trusted analytics foundation—particularly in the HR domain.

This is a great opportunity for engineers who are passionate about dbt, care deeply about data quality and usability, and are excited about contributing to a mission-driven HR-tech product.

Responsibilities

• Data Modeling & dbt Development: Design and implement high-quality, scalable, and well-documented data models using dbt, aligning with business goals and analytics use cases.
• Pipeline Ownership: Build and maintain reliable ELT pipelines in close collaboration with data engineers, ensuring smooth, automated, and testable data flows.
• HR Data Understanding: Deeply understand HR-related data such as employee records, payroll, attendance, etc., and convert business requirements into actionable datasets.
• Data Quality Assurance: Implement and maintain automated data testing, monitoring, and validation to ensure consistent and trusted data delivery.
• Cross-functional Collaboration:
  • Partner with product managers and business analysts to translate requirements into well-modeled datasets.
  • Collaborate with engineers to ensure smooth integration between data systems and product features.
• Documentation & Enablement: Produce clear documentation to support internal engineers and business users in using the data models confidently.
• Scalability & Maintenance: Continuously optimize model performance and transformation logic for large-scale HR datasets.

Requirements

Technical Skills

Must Have:

• 3+ years of experience in analytics engineering, data engineering, or BI roles.
• Proven expertise with dbt for building and managing data transformations in production environments.
• Advanced SQL skills with experience optimizing queries and building layered data models.
• Solid understanding of dimensional data modeling (e.g., star/snowflake schema).
• Experience working with cloud data warehouses (e.g., Amazon Redshift, BigQuery, or Snowflake).
• Familiarity with data testing, CI/CD, and data version control best practices (e.g., using Git).
• Ability to translate business requirements into robust, scalable, and reusable data models.

Nice to Have:

• Experience working with HR domain data (e.g., organization structures, payroll, leave management).
• Hands-on experience with Python for automation or data-related scripting tasks.
• Familiarity with Airflow, Cloud Composer, or other orchestration tools.
• Experience using Terraform or similar IaC tools.
• Knowledge of BI tools like Looker, Tableau, or Redash.
• Experience working in a multi-tenant SaaS environment.

Communication

• Strong interpersonal and communication skills with experience working in cross-functional teams.
• Enthusiastic about mentoring and supporting the growth of other engineers.
• High level of ownership and accountability.
• Business-level English proficiency (reading and writing required; conversational ability is a plus).

Skill Tags

Analytics Engineering, dbt, SQL, Data Modeling, Redshift, HR Tech, ELT Pipelines, Python, Data Quality