QC Specialist - Data Specialist (Databricks / Snowflake / Power BI)

3 - 5 years

4 - 8 Lacs

Posted:Just now| Platform: Naukri logo

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Job Type

Full Time

Job Description

The Data Specialist evaluates learners technical proficiency in data engineering, analytics, and cloud data platforms. This role involves comprehensive assessment across SQL, data pipeline development, data modeling, and visualization capabilities, while providing actionable feedback to accelerate learner development. . The specialist collaborates closely with trainers and cross-functional teams to uphold quality standards throughout the training lifecycle.
 
Responsibilities:
  • Design and execute quality audit frameworks for professional training programs
  • Conduct structured technical interviews to evaluate learners proficiency in SQL, data engineering principles, Databricks, Snowflake, and Power BI.
  • Develop comprehensive assessments including quizzes and coding challenges and practical exercises to evaluate learners understanding of the concepts and ability to apply them
  • Review and validate coding challenges by validating SQL queries, Python scripts, and data transformation logic, ensuring adherence to best practices and industry standards.
  • Evaluate end-to-end data engineering and analytics projects, including ETL/ELT pipelines, data models, and Power BI dashboards.
  • Deliver clear, actionable feedback that identifies strengths and provides guidance for technical skill enhancement.
  • Document assessment outcomes, interview insights, and performance trends systematically
  • Collaborate with trainers to share insights on learner performance and work towards enhancing training outcomes.
Experience and Skills Required:
  • 3-5 years of experience as a Data Engineer, Data Analyst, , or comparable technical role.
  • Strong proficiency in SQL, data modeling, and data analysis.
  • Experience with Databricks, Snowflake, and Power BI (experience with Tableau or Spark is an added advantage).
  • Good understanding of ETL/ELT pipelines, DataOps, and data warehousing best practices.
  • Familiarity with Python or R for scripting, data validation, or analysis.
  • Working knowledge of cloud platforms like AWS, Azure, or GCP.
  • Strong analytical thinking, attention to detail, communication, and coaching abilities

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