AWS Data Engineer

Qode; United States; Remote; USD 120,000 - 150,000; Full time

Job summary

A leading data engineering firm is seeking an experienced AWS Data Engineer to join their remote team. The role involves designing, developing, and maintaining scalable data pipelines on AWS, while collaborating with various stakeholders to ensure data integrity and performance. The ideal candidate has over 10 years of experience in data engineering, leveraging AWS technologies, and will be responsible for managing data quality and optimizing ETL processes. Competitive compensation and a fully remote work environment are offered.

Qualifications

• 10+ years’ experience with AWS native technologies.
• Experience in the design and development of scalable data pipelines.
• Proficiency in Snowflake for data transformations.

Responsibilities

• Lead data platform modernization projects.
• Develop robust data pipelines using AWS services.
• Migrate workflows from on-premise to AWS cloud.

Skills

AWS native technologies (AWS Glue, Python, Snowflake, S3, Redshift)

Data pipeline design and development

Snowflake for data transformations

Problem-solving and analytical skills

DataOps concepts and tooling

Education

Graduate/Post-Graduate degree in Computer Science or a related field

Tools

Databricks

AWS Glue

Power BI

Tableau

QuickSight

Job description

# AWS Data Engineer**Remote**Full time785d019a-e687-42e7-8685-61bbf5e35196United States## Description**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