Data Analytics Engineer (Finance)

Stori; Ciudad de México; Presencial; MXN 20,000 - 30,000; Jornada completa

Descripción de la vacante

A prominent fintech company in Ciudad de México is seeking a Data Analytics Engineer. In this role, you will leverage your analytical skills to enhance financial reporting, ensuring data accuracy and compliance. Responsibilities include developing automated solutions, collaborating on new products, and ensuring data quality. The ideal candidate holds a relevant degree and has 2+ years of experience in data analytics, particularly with SQL and Python. This position offers a challenging and innovative work environment.

Formación

• Fluent English proficiency is required.
• 2+ years experience in data analytics using SQL or Python.
• Deep understanding of credit product operations.

Responsabilidades

• Develop automated solutions for accounting processes.
• Collaborate to launch products aligning with finance objectives.
• Drive adherence to data quality management principles.

Conocimientos

SQL

Python

Interpersonal skills

Problem-solving

Communication

Educación

Bachelor's degree in Engineering, Science, or related field

Descripción del empleo

Job Description

As a Data Analytics Engineer at Stori, you will leverage your analytical and technical expertise to support our finance, accounting and regulatory reporting functions. Your role will be critical in ensuring data accuracy, compliance, and the generation of reports and reconciliations processes. On any given day, you will be challenged on three types of work – Innovation, Business Intelligence, and Data Management.

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.
• 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.
• Demonstrated ability to work under pressure and to meet tight deadlines with proactive, decisiveness, and flexibility.
• English Fluent/proficient.
• 2 or more years of experience in quantitative and qualitative analysis using SQL or Python.
• 2 or more years of working experience in data analytics.
• Deep understanding of credit product operations (credit cards, loans, asset financing, etc.).
• Understanding of financial regulations and accounting principles, especially within the fintech industry.
• Experience with regulatory and compliance reporting in a financial services context.

Job Responsibilities

Innovation

• Develop and enhance data‑driven solutions for accounting processes, including the automation of reconciliations and finance reporting to improve accuracy and efficiency.
• Use Open Source/Digital technologies to mine complex, voluminous, and different varieties of data sources and platforms.
• Build well‑managed data solutions, tools, and capabilities to enable self‑service frameworks for data consumers.
• Demonstrate the ability to explore and quickly grasp new technologies to progress varied initiatives.

Business Intelligence

• Collaborate closely with teams to launch new products or features, ensuring they are aligned with finance objectives.
• Partner with the business to provide consultancy and translate the business needs to design and develop tools, techniques, metrics, and dashboards for insights and data visualization.
• Drive analysis that provides meaningful insights on business strategies.

Data Management

• Drive an understanding and adherence to the principles of data quality management, including metadata, lineage, and business definitions.
• Work with business teams to understand their needs and translate them into technical requirements.
• Work collaboratively with appropriate Tech teams to manage security mechanisms and data access governance.
• Build and execute tools to monitor and report on data quality.