✦ Luna Orbit — Data & Analytics

Big Data Engineer Lead

at S&P Global

📍 New York, NY Unknown 💰 $149K – $202K USD / year Posted March 13, 2026
Salary $149K – $202K USD / year
Type Not Specified
Experience lead
Exp. Years 8+ years
Education BS or MS degree in Computer Science or Information Technology
Category Data & Analytics

This role involves designing and maintaining scalable data pipelines and data lake environments to support analytics, AI, and machine learning initiatives within the financial sector.

  • Design data pipelines
  • Develop data lake solutions
  • Ensure data quality and governance
  • Support AI/ML projects
  • Collaborate with data science teams

The technical environment includes AWS cloud services, big data frameworks, data governance, and ML frameworks to enable enterprise data analytics and AI solutions.

The ideal candidate is a senior data engineer with extensive experience in building and managing data pipelines using AWS cloud services, with strong knowledge of data governance and machine learning frameworks, preferably in finance or related sectors.

Data PipelinesAWSPythonData LakeData Governance
TensorFlowPyTorchScikit-learnMLlib
AWSS3RedshiftEMRSparkHadoopFlinkInformaticaTalendApache NiFi
Data PipelinesAWSS3RedshiftEMRSparkHadoopFlinkPythonScalaJavaData LakeData GovernanceData QualityData LineageInformaticaTalendApache NiFiMachine LearningTensorFlowPyTorchScikit-learnMLlib
Data PipelinesAWSS3RedshiftEMRSparkHadoopFlinkPythonScalaJavaData LakeData GovernanceData QualityData LineageInformaticaTalendApache NiFiMachine LearningTensorFlowPyTorchScikit-learnMLlib
leadershipcommunicationproblem-solvingcollaboration
Industry Financial Services
Job Function Build and manage scalable data infrastructure for analytics and AI in finance
Data PipelinesAWSS3RedshiftEMRSparkHadoopFlinkPythonScalaJavaData LakeData GovernanceData QualityData LineageInformaticaTalendApache NiFiMachine LearningTensorFlowPyTorchScikit-learnMLlib

Less than 8 years of data engineering experience, Lack of AWS cloud expertise, No experience with data lake or governance

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