AWS Data Engineer
About the role
- 8+ years relevant industry and functional experience in Database and Cloud-based technologies
- Experience in building data ingestion pipelines for Structured and Unstructured data both for storage and optimal retrieval
- Experience working with Cloud data stores (specifically AWS), noSQL, Graph and Vector databases.
- Proficiency with languages such as Python, SQL, and PySparkExperience working with Databricks and Snowflake technologies
- Exposure to Machine learning and AI concepts related to RAG architecture, LLMs and embedding is a plus
- Experience with relevant code repository and project tools such as GitHub, JIRA and Confluence
- Working experience with Continuous Integration & Continuous Deployment with hands-on expertise on Jenkins, Terraform, Splunk and Dynatrace.
- Highly innovative with aptitude for foresight, systems thinking and design thinking, with a bias towards simplifying processes. xxoysbn
- Detail oriented individual with strong analytical, problem-solving, and organizational skills
- Ability to clearly communicate to both technical and business teams
- Bachelor's degree in Engineering, Computer Science or related field; Master's degree is a plus.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
