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 Amazon Web Services services including Elastic MapReduce, Elastic Compute Cloud, Simple Storage Service, and Athena.
Fluency with artificial intelligence coding assistants such as GitHub Copilot, Claude, and ChatGPT, and artificial intelligence-assisted analytics tools for coding, debugging, and query optimization, with independent understanding of the underlying logic.
Familiarity with distributed data systems, analytical frameworks, and basic prompt engineering for artificial intelligence-enabled data workflows.
Ability to perform data validation checks for accuracy, completeness, and consistency.
Ability to independently verify artificial intelligence-assisted outputs and identify discrepancies or gaps for resolution.
Ability to document data logic, assumptions, and transformations clearly to support transparency and reproducibility.
Working knowledge of artificial intelligence-enabled data processing and automation tools for large-scale data workflows.
Ability to prepare structured, artificial intelligence-ready datasets for advanced analytics, reporting, and downstream data consumption.
Familiarity with artificial intelligence-assisted data ingestion, transformation, and orchestration tools within cloud-based data platforms.
Commitment to staying current with emerging artificial intelligence-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 Amazon Web Services-based data environments such as Elastic MapReduce, Simple Storage Service, and Athena.
Conduct structured analyses to identify trends, patterns, and performance drivers.
Support investigations into anomalies or operational issues and escalate appropriately when needed.
Translate large datasets into clear, actionable insights for stakeholders.
Maintain and build recurring data workflows and pipelines 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, Geographic Information Systems Analysts, and Research and Business Intelligence teams.
Support Media, Ad Operations, and Commercial teams with data-backed inputs.
Communicate findings clearly and seek clarification when needed.
Assist in tracking key performance indicators related to performance, efficiency, and scale.
Contribute to post-campaign or operational performance reviews.
Support forecasting or modeling initiatives under guidance, including artificial intelligence and machine learning-based approaches.
Support artificial intelligence-enabled data processing and automation tools used in large-scale data workflows.
Support preparation of structured, artificial intelligence-ready datasets for advanced analytics, reporting, and downstream data consumption.
Stay current with emerging artificial intelligence-powered data engineering and analytics technologies through continuous learning, documentation, and knowledge-sharing.
Azira is a location intelligence platform built for today’s data-driven teams, transforming mobile location signals into high-confidence, privacy-first insights. Our technology helps marketing, operations, and data leaders make smarter decisions, optimize performance, and drive measurable growth. From retailers and media agencies to destination marketers and real estate teams, we deliver trusted, validated insights rooted in real-world behavior, connecting the dots between where people go and how businesses can better reach, serve, and grow their audiences.
Why This Role Matters
The Big Data Analyst – Data Solutions (India) plays a key role in transforming large and complex datasets into meaningful insights that drive data-led media solutions and business decisions. By leveraging strong analytical skills, PySpark/Python expertise, and statistical reasoning, the Analyst helps build scalable data solutions that support business growth and innovation. Working closely with senior team members, the role contributes to advanced analytics and modelling initiatives while embracing AI-powered coding and analytics tools to improve efficiency, quality, and scalability. The ability to combine AI capabilities with sound technical judgment and ownership ensures reliable, high-impact outcomes for both the team and the business.
What You’ll Do
Large-Scale Data Processing
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 & Python.
Support scalable workflows for recurring analytical needs across AWS-based data environments such as EMR, S3, and Athena.
Data Analysis & Insight Support
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.
Data Pipeline Collaboration
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.
Data Quality & Validation
Perform data validation checks to ensure accuracy and completeness.
Identify discrepancies or gaps and escalate appropriately.
Document data logic, assumptions, and transformations clearly.
Cross-Functional Collaboration
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.
Performance & Measurement Support
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.
What You Bring
2–3 years of experience in Big data analytics and experience in working with large-scale datasets.
Strong proficiency in SQL, PySpark, and Python for processing, analysing, and optimising large datasets.
Working knowledge of AWS services including EMR, EC2, S3, and Athena.
Fluency with AI coding assistants (e.g. GitHub Copilot, Claude, ChatGPT) and AI-assisted analytics tools to accelerate coding, debugging, and query optimisation, while maintaining a strong independent understanding of the underlying logic.
Familiarity with distributed data systems, analytical frameworks, and basic prompt engineering for AI-enabled data workflows.
Strong attention to detail with 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 appropriate resolution.
Clear documentation of data logic, assumptions, and transformations to support transparency and reproducibility.
AI & Advanced Analytics Support
Working knowledge of AI-enabled data processing and automation tools used to support large-scale data workflows.
Ability to support the 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.
Why You’ll Love It Here
Competitive salary
Full health and mental wellness benefits
Flexible work environment
Big opportunity, small ego, high impact
A mission you can feel good about, and a team that makes the work fun