Senior Data Engineer

LTM

$100K — $130K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3-5 years of experience in Python, Scala, and SparkSQL
  • Strong understanding of big data processing frameworks, specifically Apache Spark
  • Experience building and optimizing data pipelines
  • Ability to collaborate with cross-functional teams
  • Knowledge of data quality and consistency management
  • Familiarity with distributed computing environments

Responsibilities

  • Develop and maintain scalable data processing pipelines
  • Utilize SparkSQL to analyze and derive insights from large datasets
  • Collaborate with teams to integrate big data solutions
  • Optimize Spark jobs for performance in distributed environments
  • Conduct code reviews and mentor junior developers
  • Participate in architectural discussions for big data platforms
  • Monitor and maintain Spark clusters and data services

Benefits

  • Opportunity to work with cutting-edge big data technologies
  • Collaboration with cross-functional teams
  • Professional development and mentorship opportunities
  • Access to training on the latest advancements in big data
  • A dynamic work environment focused on efficient solutions
Full Job Description
Role description

Job Summary

Seeking a Senior professional with 3 to 5 years of experience in Python Scala and SparkSQL to design and optimize scalable big data processing solutions within the DatabricksSparkSQLScalaPythonJava ecosystem

Job Description

Develop and maintain scalable data processing pipelines using Apache Spark with Python and Scala Utilize SparkSQL to analyze large datasets and extract meaningful insights supporting datadriven decision making Collaborate with crossfunctional teams to integrate big data solutions into existing systems Optimize Spark jobs for performance and efficiency in distributed computing environments Ensure data quality and consistency across various data sources Stay updated with the latest advancements in Spark Scala Python and related big data technologies to continuously improve processing capabilities

Roles and Responsibilities

Design develop and deploy complex data processing workflows leveraging Apache Spark Scala Python and SparkSQL Write efficient reusable and maintainable code for Spark applications Troubleshoot and resolve performance bottlenecks in Spark jobs and data pipelines Collaborate with data engineers data scientists and stakeholders to translate business requirements into technical solutions Conduct code reviews and provide mentorship to junior team members on best practices and coding standards Participate in architectural discussions and contribute to the evolution of big data platforms Monitor and maintain the health availability and reliability of Spark clusters and data servicesKarat Interview mandate

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