Senior Data Engineer

• Define and implement enterprise data architecture aligned with business and technology strategies.
  
• Lead multiple data engineering teams across complex enterprise projects and cloud transformation initiatives.
  
• Design, build, and optimize scalable cloud-native data platforms and modern data ecosystems.
  
• Architect and implement Lakehouse solutions using industry best practices.
  
• Drive enterprise-wide data governance, data quality, metadata management, and security initiatives.
  
• Review solution architecture, technical designs, and code to ensure adherence to engineering standards and best practices.
  
• Collaborate with Solution Architects, Product Owners, Business Analysts, and stakeholders to translate business requirements into scalable technical solutions.
  
• Ensure platform reliability, scalability, performance, and operational excellence.
  
• Champion automation, CI/CD, Infrastructure as Code (IaC), and DataOps best practices.
  
• Mentor and coach data engineers, fostering technical excellence and continuous learning.
  
• Identify opportunities for process improvements and technology modernization.
  
• Provide technical leadership throughout the software development lifecycle, from design through deployment and support.
  

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline.
  
• 6–12 years of experience in Data Engineering, Data Platform Development, or Cloud Data Architecture.
  
• Proven experience leading enterprise-scale data engineering programs and cloud migration initiatives.
  
• Strong expertise in designing scalable, secure, and high-performance data platforms.
  
• Demonstrated experience leading and mentoring technical teams.
  
• Strong understanding of data modeling, data warehousing, Lakehouse architecture, and distributed data processing.
  
• Excellent analytical, problem-solving, and decision-making skills.
  
• Outstanding communication, stakeholder management, and client-facing skills.
  

• Experience with enterprise data governance frameworks and metadata management solutions.
  
• Knowledge of real-time streaming and event-driven architectures.
  
• Experience with Infrastructure as Code (Terraform), containerization, and orchestration technologies.
  
• Azure certifications or cloud architecture certifications are highly desirable.
  
• Familiarity with Agile, Scrum, and modern software engineering practices.
  

Requirements

• Strong programming expertise in Python and Scala
  
• Extensive experience with Apache Spark
  
• Hands-on experience with Databricks
  
• Strong knowledge of Snowflake
  
• Experience with Apache Kafka and event-driven data architectures
  
• Deep expertise in Microsoft Azure cloud services
  
• Hands-on experience with:
           Azure Data Factory (ADF)
           Azure Synapse Analytics
           Azure Data Lake Storage
  
• Strong understanding of CI/CD pipelines and DevOps practices
  
• Experience implementing DataOps methodologies
  
• Knowledge of Terraform or other Infrastructure as Code (IaC) tools is highly preferred