As a Senior Data Analyst at DiDi, you will operate as a problem solver within large-scale data ecosystems. You will be responsible for understanding upstream data pipelines, ensuring the reliability and performance of critical data systems, along with deep-diving into data issues.

You will be the bridge between Business Intelligence, Data Engineering, and global teams, taking full ownership of ambiguous problems: from detection to root cause analysis and resolution. This role is ideal for someone who thrives in complexity, is highly curious, and can independently navigate systems, teams, and data to drive impactful solutions across the organization.

This is a high-impact role for someone who is curious, persistent, and highly technical, with the ability to go deep, move fast, and solve problems that others can't.

• End-to-End Problem Solving – Own complex data issues from start to finish: identify anomalies, investigate deeply across layers (BI, ETL, infrastructure), determine root cause, and deliver scalable solutions with minimal supervision.
• Deep Dive & Root Cause Analysis – Perform structured, hypothesis-driven deep dives into data discrepancies, performance issues, and system bottlenecks. You will be going beyond surface-level analysis into pipelines, transformations, and compute layers.
• Data Infrastructure & Performance Monitoring – Monitor and analyze data platform performance (query latency, queues, compute utilization such as vCores). Identify inefficiencies and propose optimizations or scaling strategies.
• Cross-Functional & Global Collaboration – Work closely with Data Engineering, Product, and global teams (across regions and time zones) to debug issues, align on data definitions, and ensure system reliability.
• Process Optimization & Automation – Continuously improve data workflows by optimizing queries, refining data models, and automating repetitive validation or monitoring tasks.
• Documentation & Knowledge Sharing – Create clear, structured documentation of data models, issues, root causes, and solutions to enable scalability and knowledge transfer across teams.
• Stakeholder Communication –Translate complex technical findings into clear, actionable insights. Set expectations, explain trade-offs (speed vs accuracy), and influence decision-making.

• Fluent in English (mandatory) and Spanish. Ability to communicate clearly with global teams and document findings in a structured, professional manner.
• Education: Bachelor’s degree in Engineering, Computer Science, Mathematics, Statistics, or a related field.
• Experience: 4+ years in Business Intelligence, Data Analytics, or Data Enablement roles, with strong exposure to data troubleshooting and deep dives.
• Problem Solving & Ownership: Proven ability to independently solve ambiguous, complex data problems end-to-end with minimal guidance.
• Technical Skills:
  • Advanced SQL (query optimization, debugging complex transformations)
  • Strong understanding of data pipelines (ETL/ELT) and data modeling
  • Experience working with large-scale data warehouses (Hive, Spark, BigQuery, Snowflake)
  • Familiarity with data performance concepts (query optimization, partitioning, compute resources, concurrency)
  • Python or R for data validation, automation, or deeper analysis.
• Data Infrastructure Awareness: Ability to understand and troubleshoot issues related to compute resources, data queues, and system performance.
• Analytical Mindset: Strong ability to break down complex systems, identify root causes, and connect technical issues to business impact.
• Stakeholder Management: Experience working with cross-functional and international teams, aligning on priorities and driving resolution.
• Adaptability: Comfortable operating in a fast-paced, high-pressure environment with evolving priorities and incomplete information.

Nice to have

• Experience collaborating closely with data engineering teams or contributing to pipeline design and debugging.
• Familiarity with monitoring tools, logging systems, or performance tracking frameworks.
• Experience with data management or governance tools (Collibra, Alation, Atlan).

• We create customer value – We strive to always create valuable experiences for our users in everything we do. Our focus is to always innovate new experiences that are safe, pleasant, and efficient.
• We are data-driven – We are strong believers in making informed decisions, that’s why we are data-driven. We can better navigate the business landscape strategically by analyzing valuable metrics.
• We believe in Win-win Collaboration – Success is a team sport. When we work to help our partners and colleagues win, we win, too. While keeping everyone's best interest at heart, we communicate with candor and execute with excellence in all we do.
• We believe in integrity – Integrity is at the very core of our business. We are people who always want to do the right thing. Our intentions are sincere, we speak our minds and listen to each other.
• We always strive to do better. That means venturing beyond our comfort zones, learning from our mistakes, and helping each other grow.
• We believe in Diversity and Inclusion – Diversity is one of our biggest strengths. Our differences are what makes us distinct. We respect each other and believe in equal opportunities for all.