Data Engineer - AWS/Databricks
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Key details
- Location
- Bengaluru, KA, India
- Work style
- Onsite
- Level
- Mid level
- Job type
- Full-time
- Experience
- 3–6 yrs
- Function
- Data & ML
- Focus area
- Data engineering & Analytics
- Posted
- 5d ago
Skills
airflowawsbig datacontainerizationdata engineeringdata governancedata pipelinesdata warehousingdatabricksdockeremretljavakubernetesmachine learningnosqlpythonredshifts3scalasql
About the role
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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