Why this grade
This listing scored 54/100, which is a D. It lost the most ground on pay transparency.
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Freshness 15 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Remote clarity 8 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Role specificity 6 / 10 Whether the listing is tagged well enough to tell what the role actually is.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Pay transparency 0 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
Data Science Senior Full Time
Job Brief
As an AWS Data Engineer, your role will be to design, develop, and maintain scalable data pipelines on AWS. You will work closely with technical analysts, client stakeholders, data scientists, and other team members to ensure data quality and integrity while optimizing data storage solutions for performance and cost-efficiency. This role requires leveraging AWS native technologies and Databricks for data transformations and scalable data processing.Responsibilities
- Lead and support the delivery of data platform modernization projects.
- Design and develop robust and scalable data pipelines leveraging AWS native services.
- Optimize ETL processes, ensuring efficient data transformation.
- Migrate workflows from on-premise to AWS cloud, ensuring data quality and consistency.
- Design automations and integrations to resolve data inconsistencies and quality issues
- Perform system testing and validation to ensure successful integration and functionality.
- Implement security and compliance controls in the cloud environment.
- Ensure data quality pre- and post-migration through validation checks and addressing issues regarding completeness, consistency, and accuracy of data sets.
- Collaborate with data architects and lead developers to identify and document manual data movement workflows and design automation strategies.
Skills and Requirements
- 10+ years’ experience with a core data engineering skillset leveraging AWS native technologies (AWS Glue, Python, Snowflake, S3, Redshift).
- Experience in the design and development of robust and scalable data pipelines leveraging AWS native services.
- Proficiency in leveraging Snowflake for data transformations, optimization of ETL pipelines, and scalable data processing.
- Experience with streaming and batch data pipeline/engineering architectures.
- Familiarity with DataOps concepts and tooling for source control and setting up CI/CD pipelines on AWS.
- Hands-on experience with Databricks and a willingness to grow capabilities.
- Experience with data engineering and storage solutions (AWS Glue, EMR, Lambda, Redshift, S3).
- Strong problem-solving and analytical skills.
- Knowledge of Dataiku is needed
- Graduate/Post-Graduate degree in Computer Science or a related field.
- AWS S3 (data storage, export, recall)
- Athena (querying data lakes)
- Data pipelines (batch & near-real-time)
- Integration with external systems (FHIR)
- Secure data handling (KMS, Macie)
- Cloud-native analytics
- Multi-account, multi-region data architecture
- BI integrations: Power BI, Tableau, QuickSight
Originally posted on Himalayas
Apply for this role Opens himalayas.app — the link as listed; we have not yet verified it is the employer's own page
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Where this listing came from
- 05 Oct 2026 Himalayas first sighting
Seen on 1 board over 0 days.