Databricks Data Engineer | Think Bigger, Build Impact

thinkbridge; New York (NY); On-site; USD 120,000 - 160,000; Full time

Job summary

thinkbridge is a data engineering partner in the United States, delivering scalable data pipelines and analytics solutions using Databricks and cloud platforms.

We are seeking a Data Engineer to design and optimize ETL processes, collaborate with client teams, and ensure data quality across large datasets. Expect a growth-focused environment with opportunities to advance in Databricks, Spark, and PySpark projects.

Qualifications

• Must have: Bachelor’s degree in computer science, Data Engineering, or related field.
• 3+ years of experience in data engineering and pipeline development.
• Expertise in Databricks, Spark, and PySpark.
• Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Proficiency in Python or Scala.

Responsibilities

• Design and implement data pipelines using Databricks to process and transform large-scale datasets.
• Collaborate with the client's technical teams to gather requirements and create customized data solutions.
• Optimize Databricks clusters for performance, reliability, and cost efficiency.
• Implement ETL processes to ensure data quality, security, and accuracy.
• Provide guidance on best practices for leveraging Databricks for analytics and data engineering.
• Troubleshoot and resolve issues in data workflows and platform configurations.
• Stay updated with the latest Databricks features and industry trends to recommend innovative solutions.

Skills

Data engineering mindset

Analytical thinking

Cross-functional collaboration

Education

Bachelor’s degree in computer science or related field

Tools

Databricks

Spark

PySpark

Python

Scala

AWS

Azure

Google Cloud

ETL

Data Warehousing

Job description

thinkbridge is a data engineering partner in the United States, delivering scalable data pipelines and analytics solutions using Databricks and cloud platforms.

We are seeking a Data Engineer to design and optimize ETL processes, collaborate with client teams, and ensure data quality across large datasets. Expect a growth-focused environment with opportunities to advance in Databricks, Spark, and PySpark projects.