Sicredi

Data Engineering Specialist

Sicredi

full-time

Posted on:

Location Type: Hybrid

Location: Brasil

Visit company website

Explore more

✨ AI Apply
Apply

Tech Stack

AWSPythonSQL

About the role

  • Act as the technical reference for the evolution of the Data & AI Platform, ensuring alignment with the defined target architecture.
  • Develop and implement tools, standards and capabilities that increase efficiency, governance and scalability of the data ecosystem.
  • Ensure reliability, security, resilience and observability of the solutions that compose the platform.
  • Support architects and engineers in defining technical roadmaps, engineering standards and long-term decisions.
  • Collaborate with engineering, architecture, product and business teams to ensure delivered solutions meet real needs with quality and performance.
  • Guide and enable platform consumer teams by disseminating best practices, documentation, tools and usage guidelines.
  • Promote efficient use of platform capabilities, encouraging automation, reuse and standardization.
  • Plan and execute modernization, technology upgrades and migration initiatives toward the target architecture.
  • Identify opportunities for technical and structural improvement, proposing solutions that increase productivity and reduce complexity.
  • Monitor platform component performance, anticipating risks and proactively addressing issues.
  • Ensure modern engineering practices (CI/CD, IaC, version control, automation, testing, governance) are applied across platform solutions.
  • Document solutions, standards, architectures and workflows, ensuring clarity and consistency across the organization.
  • Actively contribute to a culture of engineering excellence, collaboration and continuous improvement.
  • Research and evaluate emerging technologies, market trends and innovation opportunities that can strengthen the platform.
  • Support operational and sustainment processes, collaborating with responsible teams and assisting with the resolution of complex incidents.
  • Facilitate integration across cross-functional teams, acting as a technical bridge between specialists, consumers and stakeholders.

Requirements

  • Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Systems Analysis and Development or a related field.
  • Strong knowledge of Data Engineering concepts and practices, including pipelines, modeling, data quality, observability and data governance.
  • Solid experience with Databricks (required), including use of notebooks, Delta Lake, clusters, jobs and performance best practices.
  • Deep knowledge of modern data architectures (Data Lakehouse, Streaming, DataOps, MLOps).
  • Experience with languages and frameworks for data engineering, preferably Python, SQL and automation tools.
  • Familiarity with cloud technologies and services, especially AWS.
  • Use of modern engineering practices such as CI/CD, IaC, version control and automation.
  • Understanding of data security, privacy, governance and enterprise architecture principles.
  • Critical analytical skills, clear communication and ability to work collaboratively across multiple teams.
Benefits
  • Fixed 14th and 15th salaries
  • Profit-sharing / Results participation (based on seniority)
  • Health and dental plans with no copayment
  • Wellness programs via Wellhub (formerly Gympass): nutrition, psychology, occupational health, massage, running group and local gym
  • Meal and food allowance with flexible allocation between VA/VR cards, no copayment
  • Extended maternity and paternity leave
  • Childcare or nanny allowance for children up to 6 years and 11 months
  • Allowance for children with disabilities, no age limit
  • Life insurance
  • Private pension plan up to 8% of salary
  • Training platform – Sicredi Aprende, offering a variety of courses
  • 40-hour workweek – using a time-bank system
  • Remote work allowance (except for positions that require 100% on-site presence).
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
Data EngineeringData PipelinesData ModelingData QualityData ObservabilityData GovernanceDatabricksPythonSQLAutomation Tools
Soft Skills
Critical Analytical SkillsClear CommunicationCollaborationTechnical ReferenceProblem SolvingDocumentationContinuous ImprovementBest Practices DisseminationCross-Functional IntegrationStakeholder Engagement