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2 Days ago

Data Engineer AI

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Pune, Maharashtra, India
Information Technology
Full-Time
Thermo Fisher Scientific

Overview

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

About Company:

We help our customers accelerate life sciences research, tackle sophisticated analytical challenges, improve patient diagnostics, deliver medicines to market, and increase laboratory efficiency.

Team Description: We are the Automation, AI, and Data (AAD) team specializing in delivering data engineering and analytics, automation, and AI solutions to diverse groups and divisions across Thermo Fisher Scientific.

Responsibilities:

  • Perform data analysis, exploration, and preparation to support business use cases.
  • Build and develop data pipelines in Python/Databricks and collaborate with cloud data platforms.
  • Apply Generative AI techniques to compose prototypes, develop insights, and improve solutions.
  • Work with diverse teams to grasp requirements and convert them into data-driven/AI-driven results.
  • Conduct unit testing, validation, and data quality checks for datasets, pipelines, and AI outputs.
  • Build and develop RESTful APIs to enable communication between different software components.
  • Follow agile and DevOps practices for continuous development, testing, and deployment.
  • Contribute to data governance, documentation, and guidelines for balanced data and AI solutions.

Requirements:

  • Strong proficiency in Python with 6+ years of experience, with a focus on both data engineering (pandas, PySpark, Databricks) and AI (transformers, LLM frameworks).
  • Proficient knowledge of SQL and capability to handle relational and non-relational data.
  • Familiarity with cloud platforms (AWS, Azure, or GCP) and data lake/warehouse concepts.
  • Exposure to Generative AI tools and frameworks (e.g., LangGraph, LangChain, OpenAI APIs).
  • Awareness of timely engineering, fine-tuning, embeddings, and LLM evaluation.
  • Familiarity with BI/visualization tools (Power BI, Tableau, or similar).
  • Understanding of modern practices like DataOps, MLOps or equivalent experience, and AI/GenAI Ops.
  • Strong analytical and problem-solving skills with the ability to handle ambiguity.
  • Excellent written, verbal, and interpersonal communication skills.
  • Skill in collaborating efficiently with international teams spanning various regions and time zones.
  • Curiosity to explore and implement evolving data engineering and Generative AI technologies.

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