Data Engineer

The Data Engineer handles thedesign, development, and maintenance of data pipelines, ETL processes, anddatabase management to support AI and data science initiatives. This roleinvolves ensuring data quality, scalability, and performance across all dataengineering activities.

Responsibilities and Duties

Design, develop, and maintain data pipelines, ETL processes,and database systems to support AI and data science initiatives. Collaborate with data scientists, AI / ML engineers, and otherstakeholders to understand data requirements and ensure data availability andquality. Implement data governance, security, and regulatorystandards in all data engineering activities. Optimize data pipelines and processes for scalability,performance, and cost-efficiency. Monitor and ensure the performance and reliability of datasystems, identifying and resolving issues as needed. Stay updated with the latest advancements in dataengineering technologies and best practices. Provide support and guidance to other team members asneeded. Prepare and present data engineering reports anddocumentation to senior management and stakeholders. Participate in project planning and contribute to thedevelopment of project timelines and deliverables. Perform other duties relevant to the job as assigned by theSr. Data Engineer or senior management.

Requirements

Bachelor’s degree in Data Engineering, Computer Science, ora related field Relevant certifications (e.g., Google Cloud ProfessionalData Engineer, AWS Certified Big Data – Specialty) are preferred Minimum of 3 years of experience in data engineering orrelated fields Experience in designing and implementing data pipelines, ETLprocesses, and database systems for AI or technology-focused products Strong programming skills in languages such as Python, Java,or 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, ETLprocesses, and database management Familiarity with cloud platforms (e.g., AWS, Azure, GoogleCloud) and their data services Knowledge of data governance, security, and regulatorystandards Ability to manage multiple tasks and prioritize effectively Strong attention to detail and commitment to deliveringhigh-quality work Ability to work independently and as part of a team Programming languages (e.g., Python, Java, SQL) Data engineering tools and frameworks (e.g., Apache Spark,Kafka) Data management systems (e.g., SQL, NoSQL databases) Collaboration and communication tools (e.g., Slack,Microsoft Teams)

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