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Azira

Big Data Analyst - Data Solutions

Data EngineeringUpdated on Nov 14
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • Two to three years of experience in big data analytics and working with large-scale datasets.
  • Strong proficiency in SQL, PySpark, and Python for processing, analyzing, and optimizing large datasets.
  • Working knowledge of AWS services, including EMR, EC2, S3, and Athena.
  • Fluency with AI coding assistants such as GitHub Copilot, Claude, and ChatGPT, and AI-assisted analytics tools to accelerate coding, debugging, and query optimization while maintaining an independent understanding of the underlying logic.
  • Familiarity with distributed data systems, analytical frameworks, and basic prompt engineering for AI-enabled data workflows.
  • Attention to detail and the ability to perform data validation checks to ensure accuracy, completeness, and consistency.
  • Ability to independently verify AI-assisted outputs before use and identify discrepancies or gaps for resolution.
  • Ability to document data logic, assumptions, and transformations clearly to support transparency and reproducibility.
  • Working knowledge of AI-enabled data processing and automation tools used to support large-scale data workflows.
  • Ability to support preparation of structured, AI-ready datasets for advanced analytics, reporting, and downstream data consumption.
  • Familiarity with AI-assisted data ingestion, transformation, and orchestration tools within cloud-based data platforms.
  • Commitment to staying current with emerging AI-powered data engineering and analytics technologies through continuous learning, documentation, and knowledge-sharing.

Responsibilities

  • Process and analyze high-volume datasets from multiple sources using PySpark and distributed data processing frameworks.
  • Write and optimize queries to extract, transform, and structure data using PySpark and Python.
  • Support scalable workflows for recurring analytical needs across AWS-based data environments such as EMR, S3, and Athena.
  • Conduct structured analyses to identify trends, patterns, and performance drivers.
  • Support deeper investigations into anomalies or operational issues, escalating appropriately when needed.
  • Translate large datasets into clear, actionable insights for stakeholders.
  • Maintain and build recurring data workflows and pipelines used for client deliverables and internal analytical processes, including scheduled pipelines orchestrated through workflow management systems.
  • Collaborate with senior team members to troubleshoot data processing issues.
  • Support data preparation for dashboards, reporting, and advanced analytics.
  • Perform data validation checks to ensure accuracy and completeness.
  • Identify discrepancies or gaps and escalate appropriately.
  • Document data logic, assumptions, and transformations clearly.
  • Work closely with Data Engineers, GIS Analysts, and Research & BI teams.
  • Support Media, Ad Ops, and Commercial teams with data-backed inputs.
  • Communicate findings clearly and seek clarification when needed.
  • Assist in tracking KPIs related to performance, efficiency, and scale.
  • Contribute to post-campaign or operational performance reviews.
  • Support forecasting or modeling initiatives under guidance, including AI/ML-based approaches.

About the Company

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