Description:
Job Title: Senior Data Analyst.
Job Description (in brief):
Day-to-Day Responsibilities:
Data Ownership & ETL:
- Take end-to-end ownership of high-frequency datasets including seller discoverability, catalogue quality, order funnels, SLA/TAT adherence, and compliance datasets.
- Build and maintain automated ETL pipelines using SQL, Python, and Power Automate, ensuring reliability, accuracy, and timely refresh.
- Proactively validate and optimize datasets so that stakeholders can trust them as single sources of truth.
Dashboarding & Reporting:
- Develop and manage Power BI dashboards with role-level security that provide real-time visibility into order journeys, operational performance, and category-level growth.
- Continuously improve dashboard usability, performance, and accuracy.
- Deliver automated insights mails and reports summarizing trends, anomalies, and action points for leadership and network participants.
Operational, API & Growth Analytics:
- Monitor and analyze key operational metrics: TAT breach, fill rate, cancellations, delivery aging, and SLA adherence.
- Work with API-based logs and event-driven datasets to understand order lifecycle behavior, identify drop-offs, and ensure log compliance across buyer and seller platforms.
- Build data frameworks (e.g., NP Scorecards) to evaluate participant performance across order fulfillment, SLA compliance, and customer issue resolution.
- Partner with category pods to identify order journey drop-offs, catalogue visibility issues, and growth opportunities in supply-demand alignment.
Stakeholder Engagement:
- Collaborate with internal teams to solve operational and strategic challenges through data.
- Work closely with Buyer Apps, Seller Apps, and Logistics Partners to identify and address data-driven challenges in catalogue onboarding, product discovery, order flow, and fulfillment.
- Present insights and recommendations to senior leadership and network participants in a clear and business-focused manner.
Ideal Candidate Profile:
Education & Experience:
- Masters degree in Computer Science, Statistics, Data Science, Economics, or a related quantitative field.
- 5+ years of experience in data processing and building data pipelines based on business logic.
- Should have worked on DAX queries or creating data pipelines for a BI tool.
- Preferably atleast 2 years in e-commerce, retail, or logistics analytics.
- And strong understanding of the digital commerce funnel: catalog ingestion, search & discovery, cart & checkout, order confirmation, fulfillment SLAs, and post-purchase resolution.
Technical Skills:
- Proficiency in SQL ,PostgreSQL for advanced querying, data modeling, and ETL.
- Strong experience with Power BI (dashboarding, role-level security, optimization).
- Hands-on experience in Python for data processing, automation, and statistical analysis.
- Advanced user of Excel for ad-hoc analysis and modeling.
- Familiarity with analyzing transactional or API-driven datasets (e.g., order lifecycle events, SLA tracking, compliance logs).
Behavioral & Soft Skills:
- Business-first mindset with strong problem-solving orientation.
- Ability to own datasets and dashboards end-to-end with accountability for accuracy and reliability.
- Strong communication skills to translate data into actionable business insights.
- Comfortable collaborating with cross-functional stakeholders in a fast-evolving environment.
Please noteBefore an interview, the analysts should come well prepared on how the ONDC protocol functions and how data is stitched together.
- Understand and analyze end-to-end e-commerce order flows.
- Interpret ONDCs API-driven retail and logistics contracts.
- Identify potential drop-off points or operational bottlenecks in the order journey.
- Present insights and recommendations in a clear, business-focused manner.
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