ShepHertz - Senior Data Analyst - Python/SQL/ETL

Job Title : Senior Data Analyst

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.

- 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.

Instructions :

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.

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.

Deliverable :

- Prepare a PowerPoint presentation covering :

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

- Potential drop-off points or operational challenges.

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

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.