Job Description
Industry
Staffing & Recruiting
Work Arrangement
Fully Remote
Job Type
Full-time (40 hours/week)
Work Schedule
9 AM – 5 PM EST
Locations
Philippines, Latin America
About Pearl Talent:
Pearl works with the top 1% of candidates from around the world and connects them with the best startups in the US and EU. Our clients have raised over $5B in aggregate and are backed by companies like OpenAI, a16z, and Founders Fund. They’re looking for the sharpest, hungriest candidates who they can consistently promote and work with over many years. Candidates we’ve hired have been flown out to the US and EU to work with their clients, and even promoted to roles that match folks onshore in the US.
Hear why we exist, what we believe in, and who we’re building for: Watch here
Why Work with Us?
At Pearl, we’re not just another recruiting firm—we connect you with exceptional opportunities to work alongside visionary US and EU founders. Our focus is on placing you in roles where you can grow, make an impact, and build a long-term career. We believe in creating environments where your potential is recognized, your voice matters, and your success is tied to meaningful work—not short-term perks. Joining Pearl means stepping into opportunities that challenge you, support you, and set you up for lasting success.
Role Overview:
We are hiring a Lead Data Engineer to design and own the data infrastructure that powers analytics, operations, and AI-driven systems. This role is responsible for consolidating fragmented data sources into a centralized platform while setting the technical direction for data architecture and engineering standards. You will work cross-functionally with engineering, operations, and leadership to ensure data reliability and usability across the organization. The role combines hands-on engineering with technical oversight, particularly across AI-integrated systems. This is ideal for someone who thrives in early-stage environments and can balance pragmatic execution with long-term scalability.
Your Impact
You will play a critical role in transforming fragmented data into a reliable, scalable foundation that powers business decisions and AI workflows. Your work will directly improve data accessibility, system reliability, and operational efficiency across teams. You will enable more accurate candidate matching, better hiring outcomes, and streamlined workflows through robust data pipelines. Additionally, you will elevate engineering quality by setting standards for architecture, testing, and deployment. Your contributions will ensure that AI systems are built on clean, structured, and trustworthy data.
Core Responsibilities
Data Platform Architecture & Development – 40%
- Design and implement scalable data architecture across ingestion, storage, and serving layers
- Build and maintain ETL/ELT pipelines integrating multiple SaaS platforms and internal systems
- Develop data models supporting analytics, reporting, and AI applications
- Optimize database performance, schema design, and query efficiency
- Establish documentation and data standards for cross-team usability
Engineering Oversight & Standards – 25%
- Review code and architecture decisions across the engineering team
- Define and enforce best practices for testing, documentation, and deployment
- Identify and prioritize technical debt versus rapid delivery needs
- Troubleshoot and resolve production issues across systems
AI Systems Technical Review – 20%
- Audit LLM-powered pipelines for reliability, cost efficiency, and scalability
- Review prompt structures, structured outputs, and error-handling logic
- Ensure clean and structured data flows into AI systems
- Guide improvements in embeddings, vector storage, and evaluation datasets
Data Integration & Operations – 15%
- Manage integrations with CRMs, ATS platforms, and other SaaS tools
- Handle API limitations, schema changes, and data inconsistencies
- Ensure high data quality and pipeline reliability
- Support cross-functional teams with data accessibility and insights
Must-Haves (Required)
- 5–8 years of experience in data engineering or software engineering
- At least 2–3 years building and operating production data platforms
- Strong proficiency in Python and SQL
- Experience with PostgreSQL or similar relational databases (schema design, optimization)
- Hands-on experience building ETL/ELT pipelines from SaaS APIs
- Experience with orchestration tools (Airflow, Dagster, Prefect, or similar)
- Practical understanding of LLM systems, prompt engineering, and embeddings
- Experience setting engineering standards (code review, testing, documentation)
- Experience working with AWS or GCP
- Strong written and verbal English communication skills
- Ability to work effectively in a remote, asynchronous environment
Nice-to-Haves (Preferred)
- Experience in staffing, recruitment, or HR tech environments
- Familiarity with workflow automation tools
- Experience with AI agent frameworks
- Experience integrating with CRM and ATS platforms
- Knowledge of data governance practices (lineage, cataloging, access control)
- Experience with event-driven or streaming architectures
- Familiarity with infrastructure-as-code tools
- Basic frontend experience for internal tool development
Tools Proficiency
Must-Haves (Required)
Python, SQL, PostgreSQL, Airflow, Dagster, Prefect, AWS, GCP, Google Sheets
Nice-to-Haves (Preferred)
HubSpot, Workable, N8N, Zapier, Make, LangChain, CrewAI, AutoGen, Kafka, SQS, Docker, Terraform, React, Next.js
What You’ll Gain:
- Performance Bonus
- Fully remote, forever
- Annual team retreat
- Unlimited PTO (PH Based)
- Real-world experience in recruitment marketing and sourcing
- A behind-the-scenes look at how we connect people with opportunities
- A supportive team that values your growth and ideas
Ready to Join Us?
If you’re hungry to lead, build, and scale—and you’ve done it before—then this is the opportunity you’ve been waiting for. Apply now and help us build the world’s best recruitment team!
