Senior Data Engineer

DiDi Global; Ciudad de México; Presencial; MXN 520.000 - 900.000; Jornada completa

Descripción de la vacante

DiDi Global is seeking a Senior Data Analyst to operate within large-scale data ecosystems. You will understand upstream data pipelines, ensure reliability of critical data systems, and dive into data issues.

You’ll bridge Business Intelligence, Data Engineering, and global teams to own ambiguous problems from detection to root cause resolution. This high-impact role requires curiosity, persistence, and technical depth, with the ability to navigate systems, teams, and data to drive impactful

Formación

• Fluent in English and Spanish with clear communication across global teams.
• Bachelor’s degree in Engineering, Computer Science, Mathematics, Statistics, or related field.
• 4+ years in BI/Data Analytics with data troubleshooting and deep dives.
• Proven ability to solve ambiguous, complex data problems end-to-end.
• Strong SQL skills, knowledge of ETL/ELT, data modeling, and large-scale data warehouses.

Responsabilidades

• Own complex data issues from start to finish across BI, ETL, and infrastructure.
• Conduct structured deep dives into data discrepancies and performance bottlenecks.
• Monitor and optimize data platform performance and compute resources.
• Collaborate with Data Engineering, Product, and global teams across regions.
• Automate validation tasks and refine data models for scalability.
• Document data models, issues, root causes, and solutions for knowledge transfer.
• Translate findings into clear, actionable insights for stakeholders.

Conocimientos

English

Spanish

SQL

ETL/ELT

Data modeling

Python/R

Analytical thinking

Communication

Educación

Bachelor's degree in Engineering/CS/Math/Statistics

Herramientas

Hive

Spark

BigQuery

Snowflake

Data warehouses

Descripción del empleo

Company Overview

DiDi Global Inc. is the world’s leading mobility technology platform. It offers a wide range of app-based services across markets including Asia-Pacific, Latin America and Africa, including ride hailing, taxi hailing, chauffeur, hitch and other forms of shared mobility as well as auto solutions, food delivery, intra-city freight, and financial services.

DiDi provides car owners, drivers, and delivery partners with flexible work and income opportunities. It is committed to collaborating with policymakers, the taxi industry, the automobile industry and the communities to solve the world’s transportation, environmental and employment challenges through the use of AI technology and localized smart transportation innovations. DiDi strives to create better life experiences and greater social value, by building a safe, inclusive and sustainable transportation and local services ecosystem for cities of the future.

For more information, please visit: www.didiglobal.com/news

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Team Overview

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.

Role Responsibilities

• 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.

Role Qualifications

• 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).

EEO Statement

• 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.

We are committed to building inclusive and diverse teams.

At DiDi, we believe that our differences are our biggest source of strength. That‘s why we are committed to promoting equal opportunities to all candidates and employees as an Equal Opportunity Employer.

Employment and advancement decisions at DiDi are always made based on the needs of the position and the qualifications of the candidate. We do not discriminate against any employee or applicant based on their gender, age, sexual orientation, nationality, marital status, pregnancy/maternity, disability, race, religion and beliefs, or any other status protected by applicable laws wherever we operate.

We are committed to building inclusive and diverse teams, and a workplace that is free from discrimination and harassment, because that’s how we create better products and services, make better decisions and better serve the communities we’re a part of.

I acknowledge that prior to submitting this application, I have read and accepted the Privacy Notice for Candidates which is available on https://careers.didiglobal.com/terms