Job Summary

The Sr. Data Engineer supports the design, development, and maintenance of data pipelines, ETL processes, and database systems to support AI and data science initiatives. This role involves ensuring data quality, scalability, and performance across all data engineering activities.

Responsibilities and Duties

• Support the design, development, and
  maintenance of data pipelines, ETL processes, and database systems to support
  AI and data science initiatives.
  
• Collaborate with data scientists, AI/ML
  engineers, and other stakeholders to understand data requirements and ensure
  data availability and quality.
  
• Implement data governance, security, and
  regulatory standards in all data engineering activities.
  
• Optimize data pipelines and processes for
  scalability, performance, and cost-efficiency.
  
• Monitor and ensure the performance and
  reliability of data systems, identifying and resolving issues as needed.
  
• Stay updated with the latest advancements
  in data engineering technologies and best practices.
  
• Mentor and provide guidance to junior data
  engineers and other team members.
  
• Prepare and present data engineering
  reports and documentation to senior management and stakeholders.
  
• Participate in project planning and
  contribute to the development of project timelines and deliverables.
  
• Perform other duties relevant to the job as
  assigned by the Principal Data Engineer or senior management.
  

Requirements

• Bachelor’s degree in Data Engineering,
  Computer Science, or a related field
  
• Relevant certifications (e.g., Google Cloud
  Professional Data Engineer, AWS Certified Big Data – Specialty) are preferred
  
• Minimum of 5 years of experience in data
  engineering or related fields
  
• Experience in designing and implementing
  data pipelines, ETL processes, and database systems for AI or
  technology-focused products
  
• Strong programming skills in languages such
  as Python, SQL
  
• Proficiency in data engineering tools and
  frameworks (e.g., Apache Spark, Kafka)
  
• Excellent problem-solving and analytical
  skills
  
• Strong communication and interpersonal
  skills
  
• Attention to detail and commitment to
  quality
  
• In-depth understanding of data engineering
  principles, ETL processes, and database management
  
• Familiarity with cloud platforms (e.g.,
  AWS, Azure, Google Cloud) and their data services
  
• Knowledge of data governance, security, and
  regulatory standards
  
• Ability to manage multiple tasks and
  prioritize effectively
  
• Strong attention to detail and commitment
  to delivering high-quality work
  
• Ability to work independently and as part
  of a team
  
• Programming languages (e.g., Python, SQL)
  
• Data engineering tools and frameworks
  (e.g., Apache Spark, Kafka)
  
• Cloud platforms (e.g., AWS, Azure, Google
  Cloud)
  
• Data management systems (e.g., SQL, NoSQL
  databases)
  
• Collaboration and communication tools
  (e.g., Slack, Microsoft Teams)
  
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