About Us

Arrive, including brands like EasyPark, Flowbird, RingGo, ParkMobile and Parkopedia, is a leading global mobility platform. Present in over 90 countries and 20,000 cities, the company helps people and decision-makers make smarter decisions about urban mobility and ease the experience of travel worldwide.

Arrive delivers a unique combination of the core ingredients to make cities more livable: from smart payments and optimized car parks to data-driven traffic reduction and support for reinvestment in public transport and green space. It’s about more than function, it’s about saving time and simplifying the experience of travel for everyone. Travel is more than a journey; it’s how you Arrive.

• Learn more about us at: https://arrive.com/en

As Arrive, we guide customers and communities towards brighter futures and more liveable cities. It isn’t a challenge just anyone could take on. Luckily, we have something to help us make it happen: our people and our values. We Arrive Curious, Focused and Together. Just as our entire brand is inspired by the North Star, the shining light leading travellers to their destinations since time began, our values guide us. They help us be at our best. For our customers. For the cities and communities we serve. For ourselves. As a global team, we are transforming urban mobility. Let’s grow better together.

🎯 Role Overview

We are looking for a Senior Data Analyst to join our Revenue Operations organization, with a strong focus on large-scale CRM and lead data management. This role is designed for someone who thrives in complex data environments, enjoys building robust data foundations, and can turn messy, high-volume data into structured, reliable, and actionable datasets.

You will be a key owner of lead and customer data quality, working across CRM, marketing, and revenue systems to design and maintain data cleansing models, customer segmentation frameworks, and scalable data structures. Your work will directly support sales performance, go-to-market strategy, and revenue forecasting.

• Department: Revenue Operations

• Reporting To: Revenue Operations Leadership

• Key Partners: Revenue Operations, Sales, Marketing, Finance, and Data teams

📝 What You'll Do

🧹 Large-Scale Data Management & Data Quality

• Data Ownership: Own and manage high-volume datasets, with a particular focus on leads, accounts, contacts, and opportunities.

• Cleansing & Validation: Design and implement data cleansing models to handle deduplication, normalization, enrichment, and validation at scale.

• Standards Enforcing: Define and enforce data quality standards (completeness, accuracy, consistency, timeliness) across revenue systems.

• Monitoring & Audits: Monitor data quality through automated checks and recurring audits, and proactively address issues.

📊 Customer Segmentation & Data Modeling

• Model Maintenance: Build and maintain customer and lead segmentation models based on firmographics, behavior, lifecycle stage, and revenue attributes.

• Relationship Design: Design complex data relationships between leads, accounts, contacts, opportunities, products, and territories.

• GTM Alignment: Partner with Marketing and Sales to align segmentation logic with GTM and routing strategies.

• Scalability: Ensure segmentation and data models scale with business growth and evolving use cases.

🏗️ CRM, Revenue Systems & Data Architecture

• Subject-Matter Expertise: Act as a senior contributor and subject-matter expert for CRM data structures (Salesforce preferred).

• Architecture Influence: Support and influence CRM configuration from a data architecture perspective (objects, relationships, keys, hierarchies).

• System Reconciliation: Lead data validation and reconciliation efforts across CRM, marketing automation, and downstream BI systems.

• Migration Support: Support CRM migrations or major data initiatives, ensuring data integrity end-to-end.

📈 Analytics, Reporting & Enablement

• Dataset Delivery: Deliver reliable datasets that power dashboards, forecasting, and advanced analytics.

• Self-Service Support: Partner with BI teams to ensure clean, well-modeled data for self-service analytics.

• Data Enablement: Provide expert guidance on data interpretation, limitations, and best practices.

• Scalable Solutions: Translate business requirements into scalable data solutions rather than one-off fixes.

🛠️ Required Skills & Experience

• Experience: 5-8 years of experience in data analytics, revenue operations, or CRM data management.

• CRM Expertise: Strong hands-on experience with Salesforce (or similar CRM platforms), including deep understanding of objects, relationships, hierarchies, and data models.

• Data Management & Quality: Proven experience managing large-scale datasets (leads, accounts, contacts, opportunities) with a focus on data cleansing, duplication, normalization, and enrichment.

• Advanced Tech Stack: * Advanced proficiency in SQL for querying, transforming, and validating large datasets.

  • Experience in DBT (Data Build Tool) is a MUST.

  • Data modelling for Looker Reporting or for Data360.

  • Experience in Python is good to have.

• Segmentation & GTM Alignment: Experience designing customer and lead segmentation frameworks aligned with go-to-market (GTM), routing, and sales strategies.

• Revenue Systems Knowledge: Familiarity with marketing automation platforms (e.g., Marketo, HubSpot) and how they integrate with CRM and downstream analytics systems.

• Data Validation & Reconciliation: Experience performing data audits, validation checks, and reconciliation across multiple systems (CRM, marketing, BI tools).

• Analytics & BI Collaboration: Experience working with BI tools (e.g., Looker, Tableau, Power BI) and partnering with analytics teams to deliver clean, reliable datasets for reporting and forecasting.

• Automation & Scalability: Ability to design scalable data processes and automated quality checks, avoiding manual data handling wherever possible.

• Business Translation: Strong ability to translate business requirements into structured data solutions rather than one-off analyses.

• Stakeholder Management & Communication: * Experience working closely with Sales, Marketing, Finance, and RevOps teams to align data structures with business needs.

  • Excellent communication skills with the ability to explain data concepts, limitations, and insights to non-technical stakeholders.

• Problem Solving: Strong analytical thinking with a focus on root cause analysis and long-term data quality improvements.

Department

Operations

Locations

Bengaluru

Remote status

Hybrid

Employment type

Full-time