Data Analytics Engineer

Stori; Ciudad de México; Presencial; MXN 30,000 - 45,000; Jornada completa

Descripción de la vacante

A leading financial technology company in Mexico City is seeking a Data Analytics Engineer. This role involves building scalable data products and dashboards to enhance customer engagement in the credit card sector. The ideal candidate will possess strong SQL and Python skills and have experience in data analytics, working collaboratively with various teams to drive data-informed decisions.

Formación

• 1+ years experience in data analytics.
• Advanced skills in SQL and Python.
• Fluent in English.

Responsabilidades

• Build and maintain data pipelines for credit card engagement.
• Design automated data solutions for reporting.
• Develop dashboards and analytical reports.

Conocimientos

SQL

Python

Data Analysis

Communication

Collaboration

Educación

Bachelor's degree in a related field

Herramientas

DBT

Apache Airflow

Braze

Descripción del empleo

Job Description

As a Data Analytics Engineer on the Credit Card team, you will play a critical role in driving Stori’s data strategy to support our core credit card business. You will build scalable data products and dashboards to power credit card customer engagement, and create a reliable data infrastructure for credit card product data.

This role sits at the intersection of data engineering, analytics, and product strategy. You’ll work closely with cross-functional stakeholders across Product, Risk, Credit Policy, and Strategy to ensure they have the tools and insights to grow and optimize the credit card business.

Job Requirements

• A bachelor's degree or foreign equivalent in Engineering, Science, Operations Research, Information Technology, Statistics, Mathematics, Economics, Finance, Analytics, or a related quantitative analytical field.
• Advanced skills in SQL and Python for data manipulation and analysis.
• 1 or more years of experience in quantitative and qualitative analysis using SQL or Python.
• 1 or more years of working experience in data analytics.
• Proven interpersonal, collaboration, diplomatic, influencing, planning, and organizational skills.
• Consistently demonstrate clear and concise written and verbal communication.
• Proven ability to effectively use complex analytical, interpretive, and problem-solving techniques.
• Proven ability to work under pressure and to meet tight deadlines with proactive, decisiveness, and flexibility.
• English Fluent/proficient.

Strong Candidates may also have

• 2 or more years of experience in quantitative and qualitative analysis using SQL or Python.
• Advanced experience with DBT for data modeling and transformation
• Advanced experience with Apache Airflow (or similar orchestration tools) for building and maintaining production-grade data pipelines
• Advanced experience with Braze for customer engagement and analysis
• Deep understanding of credit product operations (credit cards, loans, asset financing, etc.).

Job Responsibilities

Key Responsibilities

Credit Product Analytics & Data Infrastructure

• Build and maintain well-managed, centralized data pipelines and data models for credit card customer engagement tracking
• Design and implement reliable, automated data solutions to streamline business reporting and operational monitoring
• Collaborate with cross-functional teams (product, risk, marketing, operations) to identify key metrics and ensure consistent definitions and alignment across teams

Business Intelligence & Insight Generation

• Develop BI dashboards, analytical reports, and data products that enable stakeholders to make data-informed decisions
• Partner with credit card product team to support experimentation, opportunity sizing, and performance deep dives
• Deliver actionable insights that influence business direction, policy changes, or feature development

Data Governance & Quality Management

• Establish and enforce data quality best practices, including definitions, lineage, validation, and access governance
• Create and maintain tools to monitor and ensure data accuracy, completeness, and consistency
• Help shape data documentation and self-service analytics for business users