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Job Title: Senior Data Engineer
What You’ll Do
Data Engineering (80%)
- Design and maintain robust data pipelines to ingest and process data from payroll, HR, and time-tracking systems
- Build and maintain clean, scalable data models (e.g., employee, pay period, hours worked)
- Set up data infrastructure in the cloud (e.g., AWS, GCP, or Azure) using tools like dbt, Airflow, Snowflake, or BigQuery
- Collaborate with the engineering team to integrate data outputs into dashboards or APIs
Data Science (20%)
· Build and test machine learning models to identify:
o Payroll anomalies (overtime spikes, duplicate pay)
o Fraud signals (ghost employees, misclassifications)
o Forecasts (payroll costs, benefits usage)
· Develop baseline models using Python (e.g., scikit-learn, XGBoost, Prophet)
· Work with product managers and payroll SMEs to translate insights into client- facing features
· Validate models and provide clear, actionable results to internal and client teams
Who You Are
- 3–6 years of experience in data engineering, data science, or a hybrid analytics role
- Proficient in Python, SQL, and modern data tools (e.g., dbt, Airflow, Snowflake/BigQuery, pandas)
- Experience building ETL pipelines and working with structured and semi- structured datasets
- Solid grasp of machine learning basics: classification, anomaly detection, time series forecasting
- Strong communication skills: you can explain technical findings to non-technical stakeholders
- Bonus: Experience in payroll, finance, HRIS, or compliance data
Nice to Have
- Familiarity with payroll/HR systems (e.g., ADP, Paychex, UKG, Workday)
- Experience with MLOps or deploying models to production
- Hands-on with dashboarding tools (e.g., Looker, Tableau, or Streamlit)
- Knowledge of privacy/security best practices with sensitive employee data
Why Join Us?
- Help build foundational AI capabilities in an industry ripe for transformation
- Work directly with the CTO, Product, and domain experts
- Influence what our AI strategy looks like from the ground up
- Flexible work, modern tools, and a culture of experimentation
Job-3335098
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