Data Engineer
@ Crossing Hurdles

Hybrid
$100,000
Hybrid
Full Time
Posted 5 days ago

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XXXXXXXXXX XXXXXXXXXXXXX XXXXXXXX******* @crossinghurdles.com
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Job Details

About the Data Engineer Role at Data Engineer

At Crossing Hurdles, we work as a referral partner referring candidates to our partners collaborating with world’s leading AI research labs to build and train cutting-edge AI models.

Role Responsibilities

  • Build robust data pipelines from diverse sources including MongoDB, Airtable, PostHog, and production databases.
  • Design dbt models and transformations to unify disparate data tables.
  • Implement scalable, fault-tolerant workflows using Fivetran, dbt, SQL, and Python.
  • Collaborate with engineers, data scientists, and business stakeholders for data availability and quality.
  • Own data quality and reliability from ingestion to consumption.
  • Continuously improve pipeline performance, monitoring, and scalability.

Requirements

  • Proven experience in data engineering with strong proficiency in SQL and Python.
  • Experience with modern data stack tools like Fivetran, dbt, Snowflake or similar platforms.
  • Skilled in building and maintaining large-scale ETL/ELT pipelines.
  • Strong understanding of data modeling, schema design, and transformation practices.
  • Familiarity with data governance, monitoring, and quality assurance.
  • Bonus: Experience supporting machine learning workflows or analytics platforms.
  • Must have access to a desktop or laptop computer (Chromebooks are not supported).

Application Process

The process takes about 15 minutes and includes uploading your resume, a 10-minute AI interview, and submitting a form.

Key skills/competency

Data pipelines, SQL, Python, ETL, dbt, Fivetran, Snowflake, data modeling, workflow scalability, collaboration

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How to Get Hired at Crossing Hurdles

🎯 Tips for Getting Hired

  • Research Crossing Hurdles culture: Understand their partner model and AI initiatives.
  • Customize your resume: Emphasize data engineering skills and projects.
  • Showcase technical experience: Highlight ETL and modern stack proficiencies.
  • Prepare for behavioral questions: Share examples of cross-team collaboration.

📝 Interview Preparation Advice

Technical Preparation

Review SQL query optimization techniques.
Practice Python scripting for ETL pipelines.
Gain hands-on with Fivetran and dbt tools.
Study data modeling and schema transformation basics.

Behavioral Questions

Share teamwork experience in prior roles.
Describe a challenging data pipeline project.
Explain collaboration with cross-functional teams.
Discuss handling deadlines under pressure.

Frequently Asked Questions