Data Engineer – Asset Management

Sicredi

. Design, build, and maintain robust data architectures focused on optimization and scalability .

Posted 9/23/2026full-timeRemote • BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining data architectures, optimizing ETLs, and implementing data pipelines for financial markets. Proficient in SQL and Python, with strong analytical and problem-solving skills to enhance data quality and governance.

Highest-signal resume keywords

Data Engineering ExperienceSQL ProficiencyPython ProficiencyDatabricks KnowledgeETL Optimization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ArchitectureData ModelingETL DevelopmentData Pipeline DesignAutomationData ManipulationAI ConceptsProcess ImprovementData QualityPerformance Optimization

Soft Skills

Analytical SkillsStrong CommunicationCollaborative Work

Tools & Technologies

DatabricksAPIsSFTPMessaging SystemsProprietary Connectors

Industry Keywords

Financial MarketData GovernanceData IntegrationRisk SystemsPerformance Systems

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Design, build, and maintain robust data architectures focused on optimization and scalability
Work on strategic projects involving migration, integration, automation, and process improvement
Design, implement, and support data pipelines connecting OMS/EMS, risk and performance systems, internal platforms, custodians, and administrators
Build data pipelines capable of identifying business opportunities from internal and external data
Build and maintain highly reliable, high-performance ETLs/ELTs
Develop integrations via APIs, SFTP, messaging, or proprietary connectors
Document processes, data flows, and technical solutions
Work with business analysts to define calculation rules, granularity, data quality, and key fields
Implement continuous improvements focused on efficiency, performance, governance, and cost optimization

Requirements

What you’ll need

Degree in Engineering, Information Systems, Computer Science, Mathematics, Statistics, or a related field
Experience in data engineering within the financial market
Solid knowledge of Databricks
Experience optimizing ETLs and configuring clusters
Proficiency in SQL and Python for data manipulation and automation
Advanced knowledge of data modeling, data architecture, and AI concepts
Analytical skills and the ability to solve complex problems related to data and technology systems
Strong communication skills and the ability to work collaboratively

Benefits

Comp & perks

Profit-sharing plan (according to seniority)
Health and dental insurance with no copayments
Wellness programs through Wellhub (formerly Gympass), including nutrition, psychology, workplace wellness, massage, a running group, and a local gym
Food and meal allowances, with flexible allocation percentages between the food and meal benefit cards and no copayments
Extended maternity and paternity leave
Childcare or nanny assistance for children up to 6 years and 11 months old
Assistance for children with disabilities, with no age limit
Life insurance
Private pension plan with employer contributions of up to 8% of salary
Training platform – Sicredi Aprende, offering a wide range of courses
40-hour workweek, using a time-banking system
Remote-work allowance (except for positions that are fully on-site)