✦ Luna Orbit — Data & Analytics

Data Engineer

at SoFi

📍 TX - Frisco Remote Posted March 08, 2026
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Position Details

Type Full-Time
Experience mid
Exp. Years Not specified
Education Not specified
Category Data & Analytics

About this role

This role involves designing and developing large-scale data pipelines and models to support analytics, reporting, and machine learning initiatives within the financial services sector.

Key Responsibilities

  • Design data models and pipelines
  • Develop and optimize ETL processes
  • Lead data analysis and modeling
  • Ensure data governance
  • Collaborate with cross-functional teams

Technical Overview

The environment includes big data technologies like Hadoop and Spark, cloud data platforms, ETL processes, and data governance frameworks.

Ideal Candidate

The ideal candidate is a detail-oriented data engineer with expertise in big data design, ETL processes, and data pipelines. They should have experience working with Hadoop, Spark, and cloud data platforms to support analytical and reporting needs.

Must-Have Skills

Data engineeringBig data designData pipelinesETL processesData modelingData analysisData governance

Nice-to-Have Skills

Machine learningData democratizationData visualizationCloud data platformsHadoopSpark

Tools & Platforms

HadoopSparkPythonSQLCloud platforms

Required Skills

Data engineeringBig dataData modelingETLData pipelinesData analysisData governanceHadoopSparkPythonSQLCloud platforms

Hard Skills

Data engineeringBig dataData modelingETLData pipelinesData analysisData governanceData infrastructureSQLPythonSparkHadoopCloud platforms

Soft Skills

LeadershipCollaborationProblem-solvingCommunicationDetail-orientedAgile mindset

Industry & Role

Industry Financial Services
Job Function Build and maintain scalable data pipelines and models for analytics and ML

Keywords for Your Resume

Data engineeringBig dataData modelingETLData pipelinesData analysisData governanceHadoopSparkPythonSQLCloud platforms

Deal Breakers

Lack of experience with Hadoop or Spark, No background in data engineering or ETL, Inability to work with big data technologies

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