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Data Engineering Analyst @ Iris Software

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 Data Engineering Analyst

Job Description

Job Duties & Responsibilities


  • Design & Build Data Systems: Architect and implement scalable data pipelines, lakehouse/lake/warehouse environments, APIs, and orchestration workflows to support analytics, AI/ML, and business intelligence.
  • Enable AI & ML at Scale: Partner with Data Science and AI teams to productionize ML models, automate workflows, and enable AI orchestration frameworks (e.g., MLflow, Airflow, Databricks workflows).
  • Technical Leadership: Act as a hands-on subject matter expert in Databricks, Python, Spark, and related technologiesdriving adoption of best practices and mentoring other engineers.
  • Optimize Performance: Ensure data pipelines and platforms are highly available, observable, and performant at scale through monitoring, automation, and continuous improvement.
  • Ensure Compliance & Security: Build solutions that adhere to data governance, privacy, and regulatory frameworks (HIPAA, SOC 2, GCP, GDPR) within clinical research, life sciences, and healthcare contexts.
  • Collaborate Across Functions: Work closely with platform engineering, analytics, product management, and compliance teams to deliver aligned solutions that meet enterprise needs.
  • Advance Modern Architectures: Contribute to evolving data platform strategies, including event-driven architectures, data mesh concepts, and lakehouse adoption.

Basic Qualifications

  • Bachelors degree in Computer Science, Engineering, Data Science, or equivalent practical experience.
  • 8+ years of data engineering experience in designing, implementing, and optimizing large-scale data systems.
  • Strong proficiency in Python, with production-level experience in building reusable, scalable data pipelines.
  • Hands-on expertise with Databricks (Delta Lake, Spark, MLflow), and modern orchestration frameworks (Airflow, Prefect, Dagster, etc.).
  • Proven track record of deploying and supporting AI/ML pipelines in production environments.
  • Experience with cloud platforms (AWS, Azure, or GCP) for building secure and scalable data solutions.
  • Familiarity with regulatory compliance and data governance standards in healthcare or life sciences.

Preferred Qualifications

  • Experience with event-driven systems (Kafka, Kinesis) and real-time data architectures.
  • Strong background in data modeling, lakehouse/lake/warehouse design, and query optimization.
  • Exposure to AI orchestration platforms and generative AI use cases.
  • Contributions to open-source projects or published work in data engineering/ML.
  • Agile development experience, including CI/CD, automated testing, and DevOps practices.

Job Classification

Industry: IT Services & Consulting
Functional Area / Department: Data Science & Analytics
Role Category: Data Science & Analytics - Other
Role: Data Science & Analytics - Other
Employement Type: Full time

Contact Details:

Company: Iris Software
Location(s): Pune

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Keyskills:   Generative Ai Data Engineering Snowflake Python

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