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Data Engineer @ SAP

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 Data Engineer

Job Description

 
The SAP SuccessFactors HCM Analytics team is responsible for delivering powerful, data-driven insights to help organizations optimize their HR processes. This team focuses on developing and enhancing advanced analytics tools within the SuccessFactors suite, enabling businesses to leverage workforce data for better decision-making. By providing actionable insights into talent management, employee performance, workforce trends, and organizational health, the HCM Analytics team plays a key role in driving HR transformation and improving operational efficiency. Their work supports HR leaders in aligning people strategies with business objectives, fostering a data-centric culture within the organization.
RESPONSIBILITIES:
  • Design and Build Scalable ETL Pipelines: Architect, build, and optimize large-scale ETL/ELT data pipelines, focusing on performance, scalability, and data integrity. Ensure the pipelines integrate smoothly within the larger data ecosystem.
  • Microservices Development and Maintenance: Design and implement microservices for managing data processing tasks. Build reusable and scalable services to handle various data processing needs and ensure maintainability.
  • Implement DevOps Practices : Utilize DevOps tools and practices (CI/CD) for automating testing, building, and deployment of data pipelines and microservices. Ensure that data workflows, models, and infrastructure are robust and can scale in a cloud-native environment.
  • Data Integration and Transformation : Collaborate with cross-functional teams to design seamless data integrations between the Transaction system and Data Platform. Focus on data transformation, cleansing, and deduplication while ensuring the pipelines are efficient and maintainable.
  • Optimize Data Processing : Tune ETL pipeline performance, focusing on real-time data processing and optimizing for low-latency data delivery. Troubleshoot and debug complex pipeline issues in distributed systems.
  • Database and Big Data Tools Management : Work extensively with SQL for structured data and leverage big data tools like Hive, HBase, and Parquet for large-scale data storage and querying.
  • Performance Optimization Data Quality : Drive data quality initiatives including data deduplication, data transformation, and performance optimizations across data pipelines and services.
  • Collaboration and Mentorship : Partner with Data Scientists, Analysts, and Engineers to ensure seamless data integration. Provide technical leadership, mentorship, and guidance to junior engineers, fostering best practices in both data engineering and DevOps.
SKILLS COMPETIENCES:
  • Strong expertise in Python, Java, or Scala for building scalable data pipelines and microservices.
  • Proven experience working with Apache Spark, Kafka, and Airflow for building data workflows and processing large datasets.
  • Strong knowledge of SQL for querying structured data and interacting with databases.
  • Hands-on experience with microservices architecture for building, deploying, and managing data services.
  • Experience working in a DevOps environment using tools like Jenkins, Git, Docker, and Kubernetes to support continuous integration and delivery.
  • Expertise in big data tools such as Hive, HBase, Parquet, and other storage solutions for managing large volumes of data.
  • Hands-on experience with data transformation, deduplication, performance optimization, and distributed systems.
  • Familiarity with Machine Learning workflow integration and automating ML data pipelines.
  • Ability to architect and scale microservices for high-volume data workloads.
  • Strong problem-solving skills with a focus on troubleshooting and debugging in a distributed data environment.
  • Experience in mentoring and providing technical leadership to junior engineers in data engineering and DevOps practices
WORK EXPERIENCE EDUCATION :
  • Requires 5+ years of professional experience is essential for understanding system architecture, programming, and technical troubleshooting.
  • Outstanding written and verbal communication skills.
  • Bachelors/master s in computer science required.

Job Classification

Industry: Software Product
Functional Area / Department: Data Science & Analytics,
Role Category: Data Science & Machine Learning
Role: Data Engineer
Employement Type: Full time

Contact Details:

Company: SAP
Location(s): Bengaluru

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Keyskills:   Computer science System architecture Software design Machine learning Workflow Data quality Distribution system Analytics SQL Python

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