Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build data pipelines and ensure high-quality performance evaluation for AI agents.
- Company: Join Mercor, connecting top talent with leading AI research labs.
- Benefits: Competitive hourly pay, remote work, and opportunities for promotion based on performance.
- Other info: Dynamic remote role with daily application reviews and support available.
- Why this job: Make a real impact in the AI field while working with cutting-edge technology.
- Qualifications: 3+ years in data engineering and expertise in pipeline orchestration and warehouse design.
The predicted salary is between 72000 - 104000 £ per year.
About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.
Position: Data Engineering Expert
Type: Contract
Compensation: $90–$125/hour
Location: Remote
Role Responsibilities
- Build long-horizon pipeline tasks with deterministic rubrics to grade agent performance against verifiable ground truth.
- Develop ETL/ELT pipelines and dbt models to produce specified output tables with incremental logic and defined watermark behavior.
- Create Airflow/Dagster DAGs that pass test suites and data quality tests with known pass/fail cases.
- Design warehouse schemas matching defined contracts and performance targets tied to measured query-time budgets.
- Work independently in long focus sessions to create challenging scenarios for agent evaluation.
- Ensure tasks have checkable answers without open-ended essays or subjective judgment calls.
Qualifications Must-Have
- BS or MS in CS or related field.
- 3+ years in data engineering or analytics engineering.
- Expertise in dbt model development, pipeline orchestration (Airflow, Dagster, Prefect), warehouse design (Snowflake, BigQuery, Redshift, Databricks), and data quality and testing.
- Comfortable with data engineering artifacts: dbt models, DAGs, schema docs, data contracts, and test suites.
- Clear written communication skills to articulate reasoning and encode it into deterministic rubrics.
Compensation & Legal
Hourly contractor. Strong contributors are promoted based on task quality and throughput.
Application Process (Takes 20–30 mins to complete)
- Upload resume
- AI interview based on your resume
- Submit form
Resources & Support
For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
For any help or support, reach out to: support@mercor.com
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
Data Engineering Expert - Pipelines employer: Mercor
Contact Detail:
Mercor Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineering Expert - Pipelines
✨Tip Number 1
Get familiar with the tools and technologies mentioned in the job description. Brush up on your dbt model development and pipeline orchestration skills, as these are crucial for the role. We want you to feel confident when discussing your experience during interviews!
✨Tip Number 2
Practice articulating your thought process clearly. Since clear communication is key, try explaining your past projects or challenges to a friend or even to yourself. This will help you convey your reasoning effectively during the AI interview.
✨Tip Number 3
Don’t underestimate the power of networking! Reach out to current employees at Mercor or similar companies on LinkedIn. A friendly chat can give you insights into the company culture and might even lead to a referral.
✨Tip Number 4
Make sure to complete your application through our website. The quicker you get your resume uploaded and AI interview done, the better your chances are. We review applications daily, so don’t miss out on this opportunity!
We think you need these skills to ace Data Engineering Expert - Pipelines
Some tips for your application 🫡
Tailor Your Resume: Make sure your resume highlights your experience in data engineering and analytics. We want to see how your skills align with the role, so don’t be shy about showcasing your expertise in dbt models and pipeline orchestration!
Craft a Clear Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for this Data Engineering Expert role. We love seeing your personality come through, so keep it professional but let your enthusiasm show!
Be Precise in Your Application: When filling out the application form, make sure to provide clear and concise answers. We appreciate straightforward communication, especially when it comes to your experience and qualifications. Remember, clarity is key!
Complete the AI Interview: Don’t forget to complete the AI interview after submitting your application! It’s a crucial step in our process, and we review applications daily. Make sure you give it your best shot to stand out from the crowd!
How to prepare for a job interview at Mercor
✨Know Your Tech Inside Out
Make sure you’re well-versed in the tools and technologies mentioned in the job description, like dbt, Airflow, and data warehousing solutions. Brush up on your knowledge of ETL/ELT processes and be ready to discuss how you've implemented these in past projects.
✨Prepare for Scenario-Based Questions
Expect to face questions that assess your problem-solving skills. Think about specific scenarios where you had to design pipelines or ensure data quality. Be ready to explain your thought process and the outcomes of your decisions.
✨Showcase Your Communication Skills
Since clear written communication is a must-have, practice articulating your ideas clearly. You might be asked to explain complex concepts simply, so prepare to demonstrate how you can encode reasoning into deterministic rubrics.
✨Familiarise Yourself with the Company
Research Mercor and its mission to connect talent with AI research labs. Understanding their values and goals will help you align your answers with what they’re looking for, showing that you’re genuinely interested in the role and the company.