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 Spark SQL
  • Proven track record in designing scalable big data solutions
  • Deep understanding of Apache Spark for data processing
  • Experience with integrating data solutions across systems
  • Familiarity with performance optimization in distributed environments
  • Knowledge of data quality assurance practices
  • Up-to-date with current big data technologies

Responsibilities

  • Design, develop, and deploy advanced data processing workflows
  • Write reusable and efficient code for Spark applications
  • Identify and resolve performance issues in data pipelines
  • Collaborate to convert business needs into technical solutions
  • Lead code reviews and mentor junior engineers
  • Engage in architectural discussions to enhance big data platforms
  • Ensure operational integrity of Spark clusters and data services

Benefits

  • Opportunities for professional development and upskilling
  • Engagement in collaborative, cross-functional projects
  • Mentorship from senior data engineering professionals
  • Exposure to cutting-edge technologies in big data
  • Flexible working hours to support work-life balance
Full Job Description
Role description

Job Title: Sr. DATA Engineer

Work Location

Irving TX

Job Description:

  • Seeking a Senior professional with 3 to 5 years of experience in Python Scala and Spark SQL to design and optimize scalable big data processing solutions within the Databricks Spark SQL Scala Python Java ecosystem
  • Develop and maintain scalable data processing pipelines using Apache Spark with Python and Scala
  • Utilize Spark SQL to analyze large datasets and extract meaningful insights supporting data driven decision making
  • Collaborate with cross functional 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 services Karat Interview mandate

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