AWS Data Engineer

Role: AWS Data Engineer

Location: NYC, NY - Onsite

Position summary :

• The Senior Data Engineer will design, build, and support data pipelines and analytics datasets that power enterprise reporting across Finance, Technology, and Operations. This role focuses on ingesting data from corporate systems, organizing it in a cloud-based data lake, and enabling reliable reporting using Amazon QuickSight.
• The ideal candidate is a hands-on data engineer who is comfortable working with modern AWS data services, partnering with business stakeholders, and supporting production reporting workloads. This role operates in a growing analytics environment and will help establish practical standards for data ingestion, modeling, and reporting.
• Context : This engineer will build and maintain Python-based ETL pipelines within AWS Glue. They will own transformation logic, manage orchestration and metadata cataloging, and ensure data is securely processed and accessible for downstream analytics and AI tools.
• The role requires strong ownership of pipeline reliability, data quality, and performance tuning.
• Experience with dbt and Snowflake will become increasingly important as the platform evolves.

Key Responsibilities

• Design, build, and maintain scalable data ingestion frameworks using AWS native services (e.g., Glue, Lambda, S3, Step Functions) and SnapLogic to data into the data lake.
• Architect and manage the enterprise data lake on Amazon S3 using Apache Iceberg, including partitioning strategies, schema evolution, metadata optimization, and lifecycle management.
• Develop robust data transformation pipelines (ELT/ETL) to standardize, cleanse, and enrich source system data for downstream analytics and operational use cases.
• Develop and maintain reporting-ready views and queries using Amazon Athena and AWS Glue metadata.
• Implement and monitor data quality frameworks, including validation rules, reconciliation checks, and anomaly detection to ensure integrity and reliability of enterprise data asset
• Collaborate with Finance, Technology, and Operations stakeholders to translate business requirements into scalable data architecture and transformation logic.
• Establish data governance best practices, including documentation, lineage tracking, access controls, and change management processes.
• Monitor pipeline health and data quality, investigate data issues, and support recurring reporting cycles.

Qualifications required :

• Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent experience.
• 7+ years of experience in data engineering, analytics engineering, or related roles.
• Strong SQL skills and experience building analytical datasets for reporting.
• Hands-on experience with AWS data platforms, including S3, Athena, Glue, AWS Unified Catalog.
• Experience integrating data from SaaS or enterprise systems using ETL tools such as SnapLogic
• Experience supporting BI tools such as Amazon QuickSight, Tableau, or Power BI.
• Ability to work independently while collaborating effectively with technical and non-technical partner

Qualifications desired:

• Experience with payment systems, networks and protocols (i.e. ISO2022, SWIFT, NACHA, etc.) is a plus.
• Experience working in a highly regulated development environment and understanding of advanced data security concepts.

Essential functions and responsibilities:

• Work with Architects, Development teams, Information Security, Infrastructure and Operations to develop requirements for common services and work with the team to create and maintain detailed functional and technical specifications and user guides.
• Ensure Common Services acts like a product with regular updates and a focus on the customer.
• Support the operation of the common components and services that the team is responsible for.
• Ensure adherence to change management and risk policies.
• Continue to drive modern enterprise application development with a focus on the cloud.

Success factors/job competencies : The candidate must be detail-oriented while also understanding the broader enterprise environment and how data supports business decision-making.


This role requires a strong team player who can work effectively across organizations and communicate clearly with technical teams, business partners, and leadership. The ability to balance hands-on execution with collaboration and operational responsibility is critical to success.

Performance standards :

• Deliver tasks and projects accurately and on schedule.
• Maintain high standards of professionalism and accountability.
• Demonstrate effective teamwork and cross-functional collaboration.
• Adhere to and support Technology & Operations and TCH strategic goals.
• Communicate clearly and effectively with internal stakeholders and external partners as needed.