Sr Manager - Data Analytics (Gurgaon)

Job Overview
We are looking for a data-driven, analytical Operations Analyst to own the monitoring, reporting, and optimization of our logistics service levels. In this role, you will be responsible for defining, tracking, and publishing core operational metrics (SLA, TAT, OTIF, First-Mile to Last-Mile delivery health). You will build dynamic, self-serve dashboards, perform granular Root Cause Analyses (RCAs) on performance failures, and work with operational heads to drive clear action plans for service recovery.

Key Responsibilities
1. Service Level Reporting & SLA Tracking

• Measure and publish daily, weekly, and monthly Service Level Agreement (SLA) reports across linehaul, hub operations, first-mile pickup, and last-mile delivery.
• Track core operational KPIs including On-Time In-Full (OTIF), Turnaround Time (TAT), First-Time Delivery Success Rate (FDR), and RTO/Breach Percentages.
• Establish automated reporting workflows to ensure timely dissemination of performance scorecards to internal stakeholders, management, and clients.

2. Root Cause Analysis (RCA) & Corrective Actions

• Investigate SLA breaches, delivery delays, and service failures across different lanes, carriers, hubs, and customer segments.
• Conduct structured Root Cause Analysis (RCA) using quantitative methodologies (e.g., 5 Whys, Pareto analysis, breach categorizations) to identify systemic operational bottlenecks.
• Present actionable recommendations, assign ownership for resolution, and follow up on corrective and preventive action (CAPA) plans with ground operations teams.

3. Dashboarding & Data Visualization

• Design, build, and maintain interactive, high-impact dashboards on tools like Power BI, Tableau, or Looker.
• Develop control tower views and early-warning alert mechanisms to flag potential SLA breaches before they impact end customers.
• Translate complex logistical data into intuitive visual insights and executive-ready slide decks for weekly and monthly performance review meetings.

4. Data Management & Cross-Functional Collaboration

• Partner with Product, Tech, and Database teams to ensure data accuracy, pipeline reliability, and standard data definitions.
• Collaborate with Regional Logistics Leads, Warehouse Operations, and Fleet Managers to review ground performance against targets.

Qualifications & Key Requirements

• Education: Bachelors degree in Engineering, Data Analytics, Statistics, Supply Chain Management, or Business Administration.
• Experience: 2–4 years of experience in business analysis, logistics performance management, or supply chain analytics (preferably in E-commerce logistics, 3PL, express parcel, or freight forwarding).
• Technical Skills:
• Data Visualization: Proven experience in building dashboards in Power BI, Tableau, or Looker.
• Data Querying & Analysis: Strong proficiency in SQL for extracting, joining, and manipulating large operational datasets.
• Advanced Excel: Mastery in Pivot Tables, complex formulas (INDEX/MATCH, XLOOKUP), conditional formatting, and macro/VBA automation.
• Python / R: Basic to intermediate knowledge for automated data cleaning or statistical modeling is a strong plus.
• Domain Knowledge: In-depth understanding of end-to-end logistics workflows, dispatch cycles, hub sorting times, and SLA definitions.
• Soft Skills: Strong presentation abilities, critical thinking, and the assertiveness needed to hold operational teams accountable for action points.