AWS Data Engineer

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🕒 January 31

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qode.world

WebsiteLinkedInAll Job Openings

11 - 50 employees

🤖 Artificial Intelligence

👥 HR Tech

🎯 Recruiter

Artificial Intelligence • HR Tech • Recruitment

qode. world is a company that leverages artificial intelligence to revolutionize the recruiting process. Their platform allows users to find candidates by sourcing data from billions of data points worldwide and provides data-driven insights. Users can connect with candidates directly through the platform, conduct customized AI-led interviews, and get comprehensive assessments. The service also integrates easily with LinkedIn, enhancing the talent pool and facilitating direct communication with candidates listed there. Qode. world offers additional recruiting services to assist in hiring for niche or senior roles. They are praised for their effectiveness in streamlining the hiring process and delivering quick results.

📋 Description

• 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.

🎯 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