Senior Data Engineer and SnapLogic

Senior Data Engineer and SnapLogic

Location: New York, USA

Employment Type: Contract

Rate: $60 on C2C

Candidate must be in East coast as this is hybrid role

Strong SnapLogic experience is required

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.

Role 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 move 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 assets.

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.

8+ 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, and 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 partners.