Design, build, maintain, and optimize scalable AWS and Databricks data pipelines and ETL processes. Collaborate with data scientists and analysts, improve data storage performance and cost efficiency, implement governance and security practices, troubleshoot pipeline issues, and recommend emerging technologies. The role requires strong programming, SQL, database, data warehousing, and big data expertise, with containerization and orchestration experience preferred.
AuxoAI is seeking a skilled and experienced Data Engineer to join our dynamic team. The ideal candidate will have
3+ years of prior experience in data engineering, with a strong background in AWS (Amazon Web Services) and
Databricks technologies. This role offers an exciting opportunity to work on diverse projects, collaborating with
cross-functional teams to design, build, and optimize data pipelines and infrastructure.
Responsibilities:
• Design, develop, and maintain scalable data pipelines and ETL processes leveraging AWS services such as S3,
Glue, EMR, Lambda, and Databricks.
• Collaborate with data scientists and analysts to understand data requirements and implement solutions that
support analytics and machine learning initiatives.
• Optimize data storage and retrieval mechanisms to ensure performance, reliability, and cost-effectiveness.
• Implement data governance and security best practices to ensure compliance and data integrity.
• Troubleshoot and debug data pipeline issues, providing timely resolution and proactive monitoring.
• Stay abreast of emerging technologies and industry trends, recommending innovative solutions to enhance
data engineering capabilities.
Requirements
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 3+ years of prior experience in data engineering, with a focus on designing and building data pipelines.
• Proficiency in Databricks, AWS services, particularly S3, Glue, EMR, Lambda, and Redshift.
• Strong programming skills in languages such as Python, Java, or Scala.
• Experience with SQL and NoSQL databases, data warehousing concepts, and big data technologies.
• Familiarity with containerization technologies (e.g., Docker, Kubernetes) and orchestration tools (e.g.,
Apache Airflow) is a plus.
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