Mô Tả Công Việc
Job DescriptionJoin 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.ResponsibilitiesData 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.
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Yêu Cầu Công Việc
RequirementsTechnical SkillsMust 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.CommunicationStrong 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 TagsAnalytics Engineering, dbt, SQL, Data Modeling, Redshift, HR Tech, ELT Pipelines, Python, Data Quality
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Hình thức
Full-time
Quyền Lợi
Caring Mental & Physical Recreation: Hybrid workingFull salary in probation & 13th month salarySocial insurance on full salary from probationPremium Health insurance from probationFlexible start 8AM-9AM from Mon-Fri16 days off annually + 1 Birthday Leave Paternity leave extra 5 days Annual company trip; Quarterly team building activitiesClub activitiesAnnual health checkCaring Career & Development: Clear Career pathForeign language & International technology-related certifications sponsoringWell-equipped facility: Macbook pro, additional monitor,..Soft skill workshopsTech seminarsMonthly and biannually Recognition AwardsPerformance review twice/year
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