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. ● 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. 2. Technical Skills ● Proficiency in SQL , Postgre SQL 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.