Data Engineer – Databricks

XEqualTo; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

XEqualTo is seeking a hands-on Data Engineer with strong Databricks, PySpark, and data pipeline development to build scalable, production-grade systems powering analytics and insights.

You will own end-to-end data workflows from ingestion to delivery, collaborating with analytics and business teams, and working in an Agile environment. This fully remote role offers the opportunity to work with a modern data stack and impact-driven projects.

Qualifications

• 4–5 years of experience in Data Engineering.
• Strong hands-on Databricks and PySpark experience.
• Advanced SQL skills and data warehousing knowledge.

Responsibilities

• Design and implement scalable data pipelines using Databricks and PySpark.
• Build ETL/ELT workflows for batch and near real-time data processing.
• Develop and maintain high-performance data models for analytics.
• Optimize data processing jobs for performance and cost.
• Collaborate with stakeholders to translate data requirements.
• Ensure data quality, validation, and monitoring.
• Participate in Agile/scrum delivery and maintain production-ready code.

Skills

Communication

Ownership

Agile/Scrum

Problem solving

Tools

Databricks

PySpark

Python

SQL

Job description

We are seeking a hands-on Data Engineer with strong expertise in Databricks, PySpark, and data pipeline development. You will be responsible for building scalable, production-grade data systems that power analytics and business insights.
This role requires someone who can own end-to-end data workflows, from ingestion to transformation and delivery, while working closely with analytics and business teams.

Key Responsibilities

• Design and implement scalable data pipelines using Databricks and PySpark
• Build robust ETL/ELT workflows for batch and (preferably) near real-time data processing
• Develop and maintain high-performance data models for analytics and reporting
• Optimize data processing jobs for performance, cost, and reliability
• Collaborate with stakeholders to understand data requirements and translate them into technical solutions
• Ensure data quality, validation, and monitoring mechanisms
• Work in an Agile environment, contributing to sprint planning, reviews, and delivery
• Maintain clean, well-documented, and production-ready code

Core Requirements

• 4-5 years of experience in Data Engineering
• Strong hands-on experience with:
  Databricks (mandatory)
  PySpark (mandatory)
  Python
  SQL (advanced level)
  Proven experience in building and managing data pipelines at scale
  Solid understanding of data warehousing and analytics concepts
  Experience working in Agile/Scrum teams

Preferred Qualifications (Good to Have)

• Experience with AWS (S3, Glue, Redshift, etc.) or Azure
  Familiarity with Medallion Architecture (Bronze/Silver/Gold layers)
• Experience with orchestration tools like Airflow
• Exposure to cost optimization and performance tuning in Databricks

Soft Skills

• Strong communication skills - ability to work with both technical and non-technical stakeholders
• High ownership and accountability in a remote work setup
• Problem-solving mindset with attention to detail

What We’re Looking For

Someone who can independently drive data engineering tasks
Comfortable working in a fast-paced, product-oriented environment
Focused on scalable, clean, and efficient data solutions rather than just scripting

Why Join Us

Fully remote role
Opportunity to work on modern data stack (Databricks + cloud)
High-impact role with ownership and growth opportunities