Senior Data Engineer

Summary:

The candidate will work on building and enhancing enterprise-scale data platforms, data pipelines, and analytical solutions. Expected deliverables include reliable data ingestion frameworks, optimized data models, automated reporting datasets, improved data quality processes, and scalable analytics infrastructure that enables business stakeholders to make data-driven decisions.

Responsibilities:

• Lead the design, development, and modernization of AWS-based data platforms, data models, and scalable data solutions supporting Finance and Travel & Expense domains.
• Drive migration of analytics workloads to centralized data platforms by performing impact assessments, architecture reviews, implementation, testing, launch, and adoption support.
• Collaborate with Finance, Product, BI, and Engineering teams to establish reusable design patterns, improve data governance, observability, operational excellence, and accelerate data-driven decision making.

Requirements:

• Bachelor's degree in Computer Science, Engineering, Information Systems, Mathematics, or related technical field.
• AWS certifications (Associate or Professional level) are preferred but not mandatory.
• 4 years of strong SQL skills and experience working with large-scale datasets.

Required Skills:

• Experience designing and building data pipelines in AWS environments.
• Hands-on experience with data warehousing concepts and dimensional modeling.
• Proficiency in Python for data engineering use cases.
• Experience with ETL/ELT frameworks and workflow orchestration.
• Strong understanding of data quality, monitoring, and performance optimization.

Preferred Skills:

• Experience with Amazon Redshift, EMR, Glue, Athena, and Lambda.
• Knowledge of Spark and distributed data processing.
• Experience with CI/CD and Infrastructure as Code.
• Exposure to machine learning pipelines and AI/GenAI applications.
• Experience with visualization tools such as QuickSight, Tableau, or Power BI.

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