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About the role
Bachelor's degree in computer science, Information Technology, Engineering, or a related field, or equivalent practical experience.
8+ years of experience in data engineering, cloud data platforms, or related software engineering roles.
Expert experience developing cloud-based data solutions using AWS technologies such as S3, Glue, Redshift, AppFlow, Lake Formation, Step Functions, and related services.
Advanced proficiency with SQL, Python, and PySpark for developing scalable ETL/ELT solutions.
Practical experience with applying AI/ML techniques to data engineering problems, such as automated data quality checks, anomaly detection, or intelligent pipeline monitoring.
Practical experience developing semantic and contextual layers within a data lake house.
Strong understanding of dimensional modeling, data warehousing, data lakehouse concepts, Apache Iceberg, Parquet, and modern data engineering practices.
Experience integrating enterprise platforms such as Salesforce, NetSuite, and other SaaS applications.
Strong understanding of modern data engineering practices with conceptual knowledge of data architecture principles, including data modeling, governance, metadata management, and scalable cloud data platforms.
Experience with Infrastructure as Code (Terraform), Git, Azure DevOps, and CI/CD pipelines.
Demonstrated ability to mentor engineers, influence technical decisions, and drive engineering best practices without formal people leadership.
Strong analytical, problem-solving, and communication skills with the ability to collaborate across technical and business teams.
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