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Senior Lead Data Engineer

Senior Lead Data Engineer

People Prime World WideIndia
30+ days ago
Job description

About Client :

Our Client is a global IT services company headquartered in Southborough, Massachusetts, USA. Founded in 1996, with a revenue of $1.8B, with 35,000+ associates worldwide, specializes in digital engineering, and IT services company helping clients modernize their technology infrastructure, adopt cloud and AI solutions, and accelerate innovation.

It partners with major firms in banking, healthcare, telecom, and media. Our Client is known for combining deep industry expertise with agile development practices, enabling scalable and cost-effective digital transformation.

The company operates in over 50 locations across more than 25 countries, has delivery centers in Asia, Europe, and North America and is backed by Baring Private Equity Asia.

Job Title : Data engineering and ETL Skills :

  • ETL, SSIS, SQL, Python, CKGL, and SAP.
  • Assist in ETL pipeline creation,SSIS packages and Python Locations : Pan : 8 - 11 Qualification : Any Mode : Type : Period : Immediate.

Job Description : Title : Senior Lead Software Engineer -Data engineering and ETL the Job :

  • Experience in ETL, SSIS, SQL, Python with PySpark.
  • Support the development and execution of reconciliation logic across EDW, FDR, CKGL, and SAP.
  • Assist in ETL pipeline creation, defect tracking, and framework maintenance under the guidance of the onshore lead.
  • Required Skills & Qualifications :

  • 4 - 6 years of hands-on experience in data engineering, MLOps, or cloud-native ML / AI systems.
  • Proficiency in Python with experience in writing production-grade code.
  • Strong experience with AWS services : SageMaker, Glue, Lambda, ECS / EKS, CloudFormation / Terraform, CloudWatch, Step Functions, S3, Redshift, Athena
  • Experience with CI / CD tools : Git, GitHub / GitLab, Jenkins, AWS CodePipeline.
  • Hands-on with Docker and container orchestration.
  • Experience working with Apache Spark / PySpark for large-scale data processing.
  • Solid understanding of machine learning lifecycle (training, validation, deployment, monitoring).
  • Strong SQL skills and experience working with large datasets.
  • Preferred Qualifications :

  • Experience with Kubeflow, MLflow, or similar MLOps frameworks.
  • Familiarity with Kafka, Airflow, or Apache NiFi for orchestration.
  • AWS Certifications (e.g., AWS Certified Machine Learning Specialty, AWS Data Analytics, or Solutions Architect).
  • Exposure to data governance, data privacy, and compliance frameworks.
  • Prior experience in Agile / Scrum environment.
  • (ref : hirist.tech)

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