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Contract Python Data Engineer (Databricks / PySpark / SQL)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Contract Python Data Engineer (Databricks / PySpark / SQL) in Columbus, IN, with a focus on optimizing data processing workflows. Requires expert Python skills, strong Databricks experience, and handling large-scale datasets. Contract length and pay rate are unspecified.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
February 11, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
On-site
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Columbus, IN
-
🧠 - Skills detailed
#Spark SQL #Batch #Debugging #NumPy #Pandas #Data Processing #PySpark #Data Science #Python #SQL (Structured Query Language) #Scala #Distributed Computing #"ETL (Extract #Transform #Load)" #Cloud #Spark (Apache Spark) #Databricks #Datasets #Data Engineering
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, AIT Global, Inc., is seeking the following. Apply via Dice today!
Job Title: Contract Python Data Engineer (Databricks / PySpark / SQL)
Location: Columbus, IN
Role Summary:
We are seeking a senior-level contract Python engineer with strong experience in Databricks-based data platforms to support and optimize large-scale analytical and data processing workflows. The role focuses on Python performance optimization, PySpark development, and SQL-based analytics in a distributed environment.
The ideal candidate is hands-on, performance-focused, and comfortable working with complex, memory-intensive pipelines.
Key Responsibilities:
• Develop and optimize Python-based data processing pipelines on Databricks
• Work extensively with PySpark DataFrames, pandas, and SQL
• Design and optimize Databricks jobs, notebooks, and workflows
• Perform runtime and memory profiling of Python and Spark workloads
• Identify and resolve:
• Memory retention issues
• Inefficient transformations
• Performance bottlenecks in large datasets
• Optimize pandas PySpark SQL data flows
• Support long-running batch and analytical jobs
• Collaborate with data scientists and engineers to improve scalability and stability
Required Skills (Must-Have):
• Expert Python
• pandas, NumPy
• Writing memory-efficient, production-quality code
• Strong Databricks experience
• Notebooks, Jobs, Clusters
• Understanding Spark execution and memory behavior
• PySpark
• DataFrame APIs
• Caching, persistence, partitioning
• SQL
• Complex joins, aggregations, window functions
• Performance optimization
• Runtime profiling
• Memory analysis and debugging
• Experience handling large-scale analytical datasets
Nice-to-Have Skills:
• Distributed computing frameworks (Spark internals, Ray, multiprocessing)
• Experience with cloud data platforms
• Familiarity with Python garbage collection and object lifecycle
• Experience supporting analytics, reporting, or reliability systems
Dice is the leading career destination for tech experts at every stage of their careers. Our client, AIT Global, Inc., is seeking the following. Apply via Dice today!
Job Title: Contract Python Data Engineer (Databricks / PySpark / SQL)
Location: Columbus, IN
Role Summary:
We are seeking a senior-level contract Python engineer with strong experience in Databricks-based data platforms to support and optimize large-scale analytical and data processing workflows. The role focuses on Python performance optimization, PySpark development, and SQL-based analytics in a distributed environment.
The ideal candidate is hands-on, performance-focused, and comfortable working with complex, memory-intensive pipelines.
Key Responsibilities:
• Develop and optimize Python-based data processing pipelines on Databricks
• Work extensively with PySpark DataFrames, pandas, and SQL
• Design and optimize Databricks jobs, notebooks, and workflows
• Perform runtime and memory profiling of Python and Spark workloads
• Identify and resolve:
• Memory retention issues
• Inefficient transformations
• Performance bottlenecks in large datasets
• Optimize pandas PySpark SQL data flows
• Support long-running batch and analytical jobs
• Collaborate with data scientists and engineers to improve scalability and stability
Required Skills (Must-Have):
• Expert Python
• pandas, NumPy
• Writing memory-efficient, production-quality code
• Strong Databricks experience
• Notebooks, Jobs, Clusters
• Understanding Spark execution and memory behavior
• PySpark
• DataFrame APIs
• Caching, persistence, partitioning
• SQL
• Complex joins, aggregations, window functions
• Performance optimization
• Runtime profiling
• Memory analysis and debugging
• Experience handling large-scale analytical datasets
Nice-to-Have Skills:
• Distributed computing frameworks (Spark internals, Ray, multiprocessing)
• Experience with cloud data platforms
• Familiarity with Python garbage collection and object lifecycle
• Experience supporting analytics, reporting, or reliability systems
