Cloud Data Engineer - SAP Cloud Ops

SAP

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profile Job Location:

São Leopoldo - Brazil

profile Monthly Salary: Not Disclosed
Posted on: 30+ days ago
Vacancies: 1 Vacancy

Job Summary

What we offer

Our company culture is focused on helping our employees enable innovation by building breakthroughs together. How We focus every day on building the foundation for tomorrow and creating a workplace that embraces differences values flexibility and is aligned to our purpose-driven and future-focused work. We offer a highly collaborative caring team environment with a strong focus on learning and development recognition for your individual contributions and a variety of benefit options for you to choose from. Apply now!

As aData Engineer you will be responsible for architecting implementing and maintaining scalable and high-performance data solutions in the Microsoft Azure ecosystem. Youll use your advanced knowledge of Azure services data engineering best practices and modern development approaches to enable data-driven decision-making across the organization.

KEY RESPONSABILITIES

1. Architect Azure Data Solutions

  • Design end-to-end cloud-native data architectures including ingestion storage processing and consumption layers.
  • Recommend Azure services aligned to scalability performance and security requirements.

2. Develop and Automate Data Pipelines

  • Build scalable data pipelines using Azure Data Factory Azure Databricks or other ETL tools.
  • Integrate data from structured semi-structured and unstructured sources using best-in-class transformation logic.

3. Model and Optimize Data

  • Design efficient data models and schemas to support analytics reporting and AI/ML use cases.
  • Optimize performance of databases and queries using partitioning indexing caching and other techniques.

4. Monitor and Maintain Systems

  • Implement monitoring logging and alerting for pipelines and storage systems using Azure Monitor Log Analytics and custom scripts.
  • Proactively identify diagnose and resolve production issues to ensure reliability and uptime.

5. Continuous Learning and Innovation

  • Stay current with emerging technologies in Azure data services.
  • Evaluate new tools and approaches to improve system efficiency scalability and cost-effectiveness.

REQUIRED QUALIFICATION

Technical Skills

  • Strong expertise in Azure data ecosystem including:
    • Storage: Azure Data Lake Storage Azure SQL Database Cosmos DB
    • Processing: Azure Synapse Analytics Azure Databricks HDInsight
    • Integration: Azure Data Factory Logic Apps
  • Proficiency in SQL Python and/or Scala for data wrangling analysis and transformation.
  • Solid knowledge of data modeling schema design and normalization techniques.
  • Hands-on experience with DevOps practices including CI/CD IaC with Azure DevOps ARM templates or Terraform.

EDUCATION

  • Bachelors or Masters degree in Computer Science Information Technology Engineering or a related discipline.

Certifications (Preferred but not required)

  • Microsoft Certified: Azure Data Engineer Associate
  • Microsoft Certified: Azure Solutions Architect Expert

EXPERIENCE

  • 3 years of experience in data engineering with a focus on cloud platforms (preferably Azure).
  • Demonstrated experience building and supporting production-grade data pipelines and analytics platforms.
  • Familiarity with Agile methodologies and cross-functional team collaboration

We are SAP

SAP innovations help more than 400000 customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software SAP has evolved to become a market leader in end-to-end business application software and related services for database analytics intelligent technologies and experience management. As a cloud company with 200 million users and more than 100000 employees worldwide we are purpose-driven and future-focused with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries people or platforms we help ensure every challenge gets the solution it deserves. At SAP we build breakthroughs together.

Our inclusion promise

SAPs culture of inclusion focus on health and well-being and flexible working models help ensure that everyone regardless of background feels included and can run at their best. At SAP we believe we are made stronger by the unique capabilities and qualities that each person brings to our company and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better and more equitable world.

SAP is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to the values of Equal Employment Opportunity and provide accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application please send an e-mail with your request to Recruiting Operations Team: Americas:or APJ: EMEA:.

EOE AA M/F/Vet/Disability:

Qualified applicants will receive consideration for employment without regard to their age race religion national origin ethnicity age gender (including pregnancy childbirth et al) sexual orientation gender identity or expression protected veteran status or disability.

Successful candidates might be required to undergo a background verification with an external vendor.

Requisition ID:431893 Work Area: Software-Design and Development Expected Travel: 0 - 10% Career Status: Professional Employment Type: Regular Full Time Additional Locations:

What we offerOur company culture is focused on helping our employees enable innovation by building breakthroughs together. How We focus every day on building the foundation for tomorrow and creating a workplace that embraces differences values flexibility and is aligned to our purpose-driven and fut...
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Key Skills

  • Apache Hive
  • S3
  • Hadoop
  • Redshift
  • Spark
  • AWS
  • Apache Pig
  • NoSQL
  • Big Data
  • Data Warehouse
  • Kafka
  • Scala

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