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Assistant Manager/Manager - Data Analyst ( IT )

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Onsite

Assistant Manager/Manager - Data Analyst ( IT )

Intas Pharmaceuticals

Assistant Manager/Manager - Data Analyst ( IT )

Skills

SQL QueriesData EngineeringData MiningPythonData ScienceNumPypandasDatabricksData AnalysisMachine LearningAIdbtApache Airflow

13 days ago

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Important information


Contract type:

Permanent

Location:

Ahmedabad, Gujarat, India

Work mode:

Onsite

Published on:

10 October 2026

What they need


Job Responsibilities

  • Develop and deploy machine learning, statistical, and predictive analytical models using Python and open-source frameworks to solve complex business problems.
  • Design solutions for processing unstructured data including documents, images, PDFs, and emails using OCR and Intelligent Document Processing technologies.
  • Build centralized data repositories, Lakehouses, and analytical datasets to support advanced analytics, AI, and enterprise reporting requirements.
  • Apply statistical techniques such as sample size determination (N), regression modelling, classification, forecasting, and hypothesis testing to generate actionable business insights.
  • Design, build, and manage analytics solutions using Microsoft Fabric components including OneLake, Lakehouse, Warehouses, and Data Pipelines .
  • Develop and optimize semantic models and analytical datasets and follow best practices.
  • Implement data ingestion, transformation, and orchestration using Fabric Dataflows Gen2 and pipelines.
  • Write and optimize SQL for analytics workloads in Fabric Warehouses and Lakehouses.
  • Implement data modeling techniques (star schema, snowflake schema) to support scalable analytics solutions.
  • Hands-on experience with Microsoft Copilot and other AI copilots for productivity and analytics.
  • Experience with data agents for query execution, workflow management, and intelligent data retrieval.
  • Ability to design and implement agent-based architectures for scalable analytics solutions.
  • Ensure data quality, validation, and governance across enterprise datasets.
  • Monitor and optimize data performance, cost, and query efficiency in Microsoft Fabric.
  • Collaborate with business and technical stakeholders to translate requirements into analytics-ready datasets.
  • Document data models, transformations, lineage, and business definitions.
  • Support ad-hoc analysis and present insights in a clear, business-friendly manner.

Required Skills & Qualifications

Technical Skills

  • Strong proficiency in Python (Pandas, NumPy, Scikit-learn, Matplotlib/Seaborn).
  • Solid understanding of data science fundamentals and applied statistics.
  • Microsoft DP-600 Certified or equivalent like Data Engineering with Spark, dbt & Airflow (Coursera) , Databricks Certified Data Engineer

Professional

  • Strong hands-on experience with Microsoft Fabric :
  • OneLake
  • Lakehouse & Warehouses
  • Dataflows Gen2
  • Data Pipelines
  • Expertise in SQL analytics and query optimization within Fabric.
  • Experience creating and managing semantic data models .
  • Knowledge of data warehousing concepts , analytical patterns, and performance tuning.
  • Familiarity with data governance, security, and access control in Fabric environments.
  • Experience working in enterprise-scale analytics platforms is a plus.

Experience & Qualifications

  • Bachelor’s degree in Engineering, Computer Science / Information Technology , MCA , BCA or related field
  • Prior experience with machine learning, statistical, and predictive analytical models and generate data insight.
  • Experience and hands on processing unstructured data including documents, images, PDFs, and emails using OCR and Intelligent Document Processing technologies
  • DP‑600 Certification is an advantage and good to have.
  • Prior experience with large-scale data platforms or cloud analytics solutions.
  • Experience working in cross-functional teams and stakeholder-facing roles

Analytical & Soft Skills

  • Strong analytical and problem-solving mindset.
  • Ability to work with complex datasets and derive actionable insights.
  • Excellent communication skills to explain technical concepts to non-technical stakeholders.
  • Strong documentation and data storytelling abilities.
  • Ability to work independently and collaboratively in cross-functional teams.

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