
$0-$0 / yr
Salary
brazil
Region
ASAP
Start Date
Pearl Talent is a US-based start-up that helps the top 1% of talent worldwide land long-term roles at fast-growing companies in the US and EU.
Founded by Monty Ngan and Isaac Kassab, Pearl Talent helps operators all around the Philippines, Latin America, and South Africa get staffed into companies backed by Y Combinator, Sequoia, a16z, General Catalyst, and more.
We believe that even though opportunity isn’t created equal in the world, ambitious talent is.
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
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
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.
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.
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.
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
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
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
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
Requirements
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
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
Python, SQL, PostgreSQL, Airflow, Dagster, Prefect, AWS, GCP, Google Sheets
HubSpot, Workable, N8N, Zapier, Make, LangChain, CrewAI, AutoGen, Kafka, SQS, Docker, Terraform, React, Next.js
Benefits
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!