Lead Data Engineer

WorkHQ; Beverly Hills (CA); Remote; USD 120,000 - 180,000; Full time

Job summary

A leading US HRTech startup is seeking a Lead Data Infrastructure Architect to manage and design data architectures for billions of data points. The role involves hiring data engineers, designing scalable data pipelines, and overseeing advanced ETL processes, requiring strong expertise in PySpark, AWS, and data optimization. Candidates with a passion for learning and leadership are encouraged to apply, especially those at Director or VP levels.

Qualifications

• 5-8 years professional data engineering experience required.
• Strong background in big data processing architectures and data warehouse design.
• Advanced skills in Python and SQL.

Responsibilities

• Design scalable data pipelines processing massive record volumes.
• Implement advanced data matching using Splink.
• Integrate new data sources into the main pipeline.

Skills

PySpark

AWS data services

Docker

Pandas

SQL

Complex data format handling

Tools

EMR

Postgres

OpenSearch

DataBricks

Snowflake

Splink

Job description

Company Context

Series A, well-funded US startup in HRTech developing WorkHQ.com and an AI Recruiter product.

This is a US-only, Remote role (Mainland).

Role Overview

Lead data infrastructure architect managing billions of data points across 250M+ professional profiles.

Hire data engineers to aid you in that journey.

Core Responsibilities

• Design scalable data pipelines processing massive record volumes

• Architect ETL processes using PySpark on Amazon EMR (Open to shifting to other solutions like Data Bricks / Snowflake)

• Distribute enriched data through medallion architecture across Postgres, Athena, OpenSearch

• Integrate new data sources into the main pipeline

• Implement advanced data matching using Splink

Technical Requirements

• 5-8 years professional data engineering experience

• Good proficiency in:

  • PySpark and distributed computing

  • AWS data services (EMR, Glue, Athena)

  • Docker

  • Pandas and DataFrame manipulation

  • Complex data format handling (JSONL, Parquet)

• Strong background in:

  • Big data processing architectures

  • Data warehouse design

  • Performance optimization

• Advanced Python, SQL skills

Nice to Have

• Probabilistic record linking expertise

• OpenSearch/elasticsearch technologies

  
  

• Machine learning data pipeline design

• Recruitment tech ecosystem knowledge

Technical Stack

• Big Data: PySpark, EMR

• Databases: Postgres, OpenSearch

• Cloud: AWS

• Containerization: Docker

• Data Formats: JSONL, Parquet

• Analytics: Metabase, Athena, Glue

• Data Processing: Pandas, Splink

Other Considerations

While this role has specific requirements - if you lack a few technical skills, but motivated to learn and lead the platform, please apply for consideration.

If you are coming from Director/Head of/VP levels that is relevant to this job, you can apply as well.

You will need to apply directly on our platform.

Thank you for your time.