Databricks Specialist With Python Java And Spark Expertise

About OpenTrain

OpenTrain AI is the hiring and contracting organization for this role. OpenTrain helps people build careers in AI training and data labeling, where skilled contributors support the development of modern artificial intelligence systems.

• Remote contract opportunity available to candidates in India, the Philippines, and Vietnam.
• Apply through OpenTrain and create an account at no cost.

About AI Training And Data Work

AI training includes the human work behind advanced technology, such as preparing data, reviewing outputs, evaluating code, and improving the systems that power AI products. Programming and data engineering specialists contribute by analyzing code and developing reliable data workflows that help AI systems learn from high-quality examples.

• Work remotely with a computer and internet connection.
• Flexible, part-time project work can fit around other commitments.
• Contributors help shape cutting-edge AI systems through technical expertise and careful evaluation.

The Databricks Specialist Role

OpenTrain is seeking a Databricks Specialist with hands-on Databricks experience and deep expertise in Apache Spark. You will develop efficient data workflows, conduct advanced data analysis, and optimize large-scale data processing systems.

The role is listed as entry level, while the detailed requirements call for at least five years of Databricks experience and at least five years with one or more supported programming languages. It is a part-time contractor position requiring 20 or more hours per week, with pay of $12 per hour.

• Contractor and part-time engagement.
• 20+ hours per week.
• Pay: $12 USD per hour.
• English proficiency at B1 or B2 level.
• Remote eligibility: India, the Philippines, and Vietnam.

What You’ll Do

You will work with Databricks and Apache Spark to support data processing, analysis, and performance optimization. The work requires practical problem-solving across data pipelines, ETL processes, codebases, and technical documentation.

• Design and optimize data pipelines, ETL processes, and data solutions using Databricks.
• Build, optimize, and troubleshoot Spark-based data processing systems.
• Develop efficient data workflows and perform advanced data analysis.
• Analyze, debug, and test large codebases.
• Optimize large-scale data processing systems and Databricks workloads.
• Navigate complex technical documentation.
• Collaborate effectively in a remote team environment while solving complex technical problems independently.

Requirements And Technical Experience

Applicants should have deep Apache Spark expertise and at least five years of experience working with Databricks. You must also have at least five years of experience in one or more of Python, Java, SQL, Scala, or Spark. Proficiency in multiple languages is preferred, but strong expertise in one qualifying language is valued.

During the interview, candidates will be asked to identify which supported languages they know and state their years of experience with each one. Candidates should also explain which core Apache Spark components they know.

• Minimum five years of Databricks experience.
• Deep expertise building, optimizing, and troubleshooting Apache Spark systems.
• At least five years with Python, Java, SQL, Scala, or Spark.
• Strong experience building and optimizing data pipelines and ETL processes.
• Hands-on Databricks experience with data processing, analysis, and performance optimization.
• Experience analyzing, debugging, and testing large codebases.
• Familiarity with Azure or AWS is preferred.
• Ability to work independently and solve complex technical problems.
• Excellent communication and remote collaboration skills.
• B1 or B2 English proficiency.

Interview And Technical Evaluation

The interview will confirm your Databricks and Apache Spark knowledge, programming language experience, and weekly availability. Candidates must answer the technical test questions at the end of the interview; the live chat interview should not end before both questions are answered. Interview evaluation will consider whether responses are correct and complete.

Candidates must also provide the number of hours per week they are available for this project. That response should be included in the interview summary.

• Explain which Apache Spark core components you know.
• List every supported programming language you know and your years of experience with each.
• State how many hours per week you are available.
• Answer both technical test questions before the interview ends.

Technical Test Questions

Question 1: Databricks Debugging and Optimization. You are given a PySpark job in Databricks that processes a large dataset, but it keeps failing with an OutOfMemoryError. What steps would you take to debug and resolve this issue? Provide specific adjustments or optimizations you would apply in Databricks to prevent memory-related issues.

Question 2: Code Review and Documentation. Imagine you are tasked with reviewing the following Python code written for a Databricks notebook: data = spark.read.csv("/path/to/file.csv", header=True) filtered_data = data.filter(data["column"] > 100) result = filtered_data.groupBy("category").count() result.show() Identify any issues or areas for improvement in this code. Write a brief description of what the code does and suggest better practices for maintainability or performance.

• Discuss debugging steps for a PySpark OutOfMemoryError.
• Recommend specific Databricks memory and performance optimizations.
• Review the supplied Python and Databricks code for issues.
• Explain the code’s behavior and suggest maintainability or performance improvements.

How To Apply Through OpenTrain

Create a free OpenTrain account and apply through the platform. Be ready to document your Databricks experience, Apache Spark components, programming languages, years of experience with each language, English level, and weekly availability. The interview will include the required technical questions and an evaluation of the completeness and correctness of your answers.

• Apply through OpenTrain for consideration.
• Prepare clear details about your technical background.
• Confirm your availability for 20 or more hours per week.
• Complete both technical interview questions.