
Senior Data Analyst
1 day ago
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.
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