AWS Data Engineer.
This mandate is run by SYMPHONI HR, a Mumbai-based executive search firm, est. 2003. Applications are email-verified and reach the search team running the role — confidentially, always.
About the organisation.
Our client is a prominent global firm in the computer software industry, known for its innovative solutions and extensive client base. They operate at a significant scale, delivering cutting-edge technology services and products worldwide. The company fosters a collaborative and dynamic work environment, emphasizing continuous learning and professional growth.
About the role.
As an AWS Data Engineer, you will be instrumental in designing, developing, and maintaining scalable data systems. This role involves working with a variety of cloud-native and open-source technologies to build robust data pipelines and platforms. You will collaborate with cross-functional engineering teams to deliver high-quality data solutions that support critical business functions.
What you will do.
- Design and support scalable distributed data systems using open-source and cloud-native technologies
- Provide technical guidance and collaborate effectively within cross-functional engineering teams
- Develop and maintain data pipelines and platforms using AWS services and Snowflake
- Apply strong object-oriented design and software engineering fundamentals to ensure maintainable architecture
- Contribute to a healthy team culture, accountability, and successful delivery outcomes
- Communicate effectively with both technical and non-technical stakeholders
- Work within Agile delivery models such as Scrum or Kanban
What you bring.
- Bachelor’s degree in Computer Science, Mathematics, Engineering, or equivalent practical experience
- 7+ years of experience in data engineering, software engineering, or data platform development
- 2+ years of hands-on experience with Snowflake
- 3+ years of experience in AWS (S3, IAM, Athena, SNS, SQS, EMR)
- 4+ years of SQL Server experience, including SSIS and SSRS
- Strong understanding of data modeling concepts and trade-offs
- Proven ability to build partnerships across diverse teams
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