Senior Data Analyst

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

1.
  
Education & Experience

●     Master's degree in Computer Science,Statistics, Data Science, Economics, or a related quantitative field.

● 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.

2.
  
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 note- Before 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 ONDC's 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.

Instructions

1. Explore ONDC GitHub

●     Visit the

ONDC GitHub page.

●     Review the latest
retail and logistics contract specifications
.

●     Understand the APIs, endpoints, and workflows for order lifecycle events.

2. Map the End-to-End Order Journey

●     Stitch together the full order journey:
product discovery → search → selection → cart → checkout → order confirmation → fulfillment → delivery

●     Highlight
interaction points between Buyer Apps, Seller Apps, and Logistics Partners
through APIs.

●     Identify potential
drop-off points or failures
that could affect the order flow.

3. Deliverable

Prepare a
PowerPoint presentation
covering:

1.    
Diagram of the end-to-end order journey
with API interactions.

2.    
Potential drop-off points or operational challenges
.

3.    
Recommendations or insights
for improving efficiency, visibility, and network performance.

4. Evaluation Criteria

Candidates will be evaluated on:

●     Understanding of e-commerce order flows and network operations.

●     Ability to interpret API contracts and event-driven workflows.

●     Analytical thinking in identifying bottlenecks or drop-offs.

●     Clarity, structure, and business focus in the presentation.

●     Practicality and creativity of recommendations.

Optional Guidance

●     Use diagrams, flowcharts, or visuals to illustrate the journey.

●     Emphasis should be on
business impact and operational insight
, not just technical details.

●     Focus on
end-to-end visibility
from product discovery to post-order resolution.