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Data Engineer - Python / SQL / ETL

Data Engineer - Python / SQL / ETL

Cognitive Stars India Pvt. Ltd.Pune
30+ days ago
Job description

Job Title : Data Engineer

Experience : 2 4 years

Key Responsibilities :

  • Architect and lead the development of scalable, reusable Python-based ETL pipelines to ingest, process, and manage data from complex enterprise systems such as SAP, OCPLM, and others.
  • Drive data transformation strategies, ensuring raw data is cleaned, enriched, and optimized for downstream analytics, machine learning models, and visualization platforms.
  • Collaborate cross-functionally with data scientists, analysts, and supply chain stakeholders to enable predictive and prescriptive analytics solutions that inform critical business decisions.
  • Mentor and guide junior data engineers, promoting best practices in data pipeline development, automation, and code quality across the team.
  • Lead initiatives in data automation, leveraging Python, cloud-native orchestration tools, and CI / CD practices to enhance efficiency and reliability.
  • Oversee cloud data engineering efforts, particularly within Azure Data Lake and Databricks environments, ensuring solutions are secure, cost-effective, and scalable.
  • Establish and enforce data governance standards, including data integrity, quality assurance, lineage tracking, and documentation throughout the pipeline lifecycle.
  • Stay abreast of advancements in AI / ML, providing structured, production-ready data to accelerate model development and deployment in supply chain contexts.
  • Influence architectural decisions, tool selection, and long-term data strategy in alignment with organizational goals.

Required Skills & Qualifications :

  • 24 years of experience in data engineering or analytical programming roles.
  • Strong programming skills in Python for data transformation and automation.
  • Good command over SQL for querying and joining large datasets.
  • Familiarity with Azure Data Lake, Databricks, or similar cloud platforms.
  • Solid analytical thinking and problem-solving ability in working with complex, real-world datasets.
  • Understanding of ML concepts like regression, classification, forecasting (hands-on not mandatory).
  • Ability to understand enterprise data structures from systems like SAP or OCPLM, even without direct system access.
  • Tools & Technologies :

  • Python, Pandas, NumPy, SQL
  • Azure Data Lake, Databricks
  • ML libraries : scikit-learn, XGBoost (as needed)
  • (ref : hirist.tech)

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