✦ Luna Orbit — Data & Analytics

Lead, Data Engineer

at Prudential Financial

📍 Newark, NJ, USA Unknown 💰 $133K – $220K USD / year Posted March 13, 2026
Salary $133K – $220K USD / year
Type Not Specified
Experience lead
Exp. Years Not specified
Education Bachelor of Computer Science or Engineering or experience in related fields
Category Data & Analytics

This role focuses on designing, developing, and maintaining high-quality data pipelines and analytics solutions to support investment reporting.

  • Build and optimize data pipelines
  • Conduct complex data analysis
  • Collaborate on data projects
  • Write automated tests
  • Coach team members

Stack includes Python, R, SQL, Java, Scala, Spark, with emphasis on data transformation, automation, and DevOps integration.

The ideal candidate is a lead data engineer with extensive experience in building data pipelines, performing data analysis, and deploying solutions using Python, R, SQL, and Spark technologies. They should have strong coaching skills and a solid understanding of SDLC and DevOps practices.

Experience in working with DevOps automation toolsKnowledge of full software development life cycle (SDLC)Ability to coach othersExperience with PythonExperience with RExperience with SQLExperience with JavaExperience with ScalaExperience with Pyspark/Apache Spark
Data analysisData pipelinesData transformationData reliabilityData quality
PythonRSQLJavaScalaPysparkApache SparkDevOps toolsJiraGitJenkins
PythonRSQLJavaScalaPysparkApache SparkData pipelinesData analysisDevOpsSDLC
PythonRSQLJavaScalaPysparkApache SparkData pipelinesData analysisData transformationDevOpsSDLC
problem solvingcommunicationteamworkagile ways of workingbusiness insightcontinuous learningcoaching
Industry Financial Services / Insurance
Job Function Data engineering and analytics development
Role Subtype Data Engineer
Tech Domains Python, SQL / PostgreSQL, Apache Spark, Machine Learning
Data EngineerPythonRSQLJavaScalaPysparkApache SparkData pipelinesData analysisDevOpsSDLCData transformationData qualityData reliability

Lack of experience with Spark or Pyspark, No experience with SDLC or DevOps tools, No experience with data pipelines

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