Overview

YES MADAMJob Description – Data Engineering & Analytics Lead

Responsibilities

• We are looking for a Data Engineering & Analytics
• Lead to build and lead our data engineering and analytics capabilities. This role will be responsible for designing scalable data pipelines, developing a reliable data platform, establishing data quality standards, and enabling actionable insights across Product, Technology, Marketing, Operations, Finance, and Business teams.
• Data Engineering & Architecture
• Design and develop scalable, reliable, and cost-efficient data architectures and data pipelines.
• Build and maintain ETL/ELT workflows to ingest, transform, validate, and process data from multiple sources.
• Develop and optimize data warehouses, data lakes, and analytical data models.
• Establish data architecture standards to support growing data volumes and real-time business requirements.
• Ensure data availability, consistency, accuracy, and reliability across systems.
• Product & Business Analytics
• Partner with Product, Engineering, Marketing, and Business teams to identify analytical requirements and build data-driven solutions.
• Develop frameworks to track product metrics, customer behaviour, user journeys, conversion funnels, retention, repeat purchases, and cohort performance.
• Enable A/B testing, experimentation, feature performance analysis, and product decision-making.
• Build analytical models to identify business opportunities, customer trends, operational bottlenecks, and growth drivers.
• Translate complex datasets into actionable insights and recommendations for leadership.
• Business Intelligence & Reporting
• Build and maintain dashboards, reports, and self-service analytics capabilities.
• Define and standardize KPIs across product, customer experience, marketing, and operations.
• Enable leadership teams to monitor business performance through reliable and timely reporting.
• Improve reporting accuracy, reduce manual reporting efforts, and establish a single source of truth for key business metrics.
• Data Quality, Governance & Security
• Establish data quality checks, monitoring mechanisms, and pipeline observability.
• Define data governance practices, documentation standards, data lineage, and access controls.
• Ensure appropriate handling of customer and business data in accordance with applicable privacy and security requirements.
• Identify and resolve data discrepancies, pipeline failures, and performance bottlenecks.
• Team Leadership & Stakeholder Management
• Lead, mentor, and develop data engineers and analytics professionals.
• Work closely with Product Managers, Engineering Leaders, Business Heads, and senior leadership.
• Prioritize data initiatives based on business impact, technical feasibility, and organizational needs.
• Drive a culture of data ownership, analytical rigor, and continuous improvement.

Qualifications

• Employment Type: Full-Time
• Work Mode: Work From Office (WFO)
• Function: Data Engineering, Analytics & Business Intelligence
• About YES MADAM
• YES MADAM is a leading D2C at-home beauty and wellness services platform, serving lakhs of customers across the country. We are a fast-moving, insight-driven organization focused on building scalable technology and delivering exceptional customer experiences.
• 8–12+ years of experience in data engineering, analytics engineering, business intelligence, or related data-focused roles.
• Strong hands-on expertise in SQL, Python, data modelling, and ETL/ELT pipeline development.
• Experience designing scalable data pipelines and modern data warehouse architectures.
• Strong understanding of data warehouses, data lakes, dimensional modelling, and analytical data models.
• Experience with cloud data platforms such as AWS, GCP, or Azure.
• Hands-on experience with technologies such as Apache Spark, Airflow, dbt, Kafka, or equivalent tools relevant to the organization's architecture.
• Experience with BI and visualization tools such as Power BI, Tableau, Looker, or equivalent.
• Strong understanding of product analytics, funnel analysis, cohort analysis, retention, experimentation, and business KPI frameworks.
• Experience leading projects and collaborating with cross-functional stakeholders.
• Strong problem-solving, communication, and people-management skills.
• Experience in a product-based organization, consumer internet, D2C, e-commerce, marketplace, or high-growth startup.
• Exposure to product analytics tools such as Mixpanel, Amplitude, or Firebase Analytics.
• Experience with real-time data processing, streaming architectures, and event-driven systems.
• Knowledge of data orchestration, CI/CD for data pipelines, data observability, and automated data testing.
• Experience with customer segmentation, personalization, recommendation systems, or predictive analytics.
• Exposure to AI/ML data pipelines, feature engineering, and data infrastructure for AI applications.
• Experience building a data platform or analytics function from the ground up.
• Reliability, performance, and scalability of data pipelines.
• Data accuracy, quality, freshness, and availability.
• Reduction in manual reporting and time required to generate insights.
• Adoption and effectiveness of dashboards and analytics solutions.
• Improved visibility into product, customer, and business KPIs.
• Ability to translate business problems into actionable data insights.
• Team productivity, stakeholder satisfaction, and timely delivery of data initiatives.