Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Metro location and generic title increase candidate density despite seniority and specialized requirements.
Core data engineering skills transferable, but compensation/payroll domain specificity increases domain bias.
Explicit 8+ years and mandatory AWS/Python data-engineering skills make shortlisting highly stringent.
Design and implement end-to-end cloud-based data pipelines and APIs primarily using Python, AWS Glue, Lambda, EventBridge, and C# to support compensation and business functionalities.
Develop and maintain ETL/ELT workflows, event-driven architectures, and data quality frameworks ensuring data integrity and performance tuning with relational databases.
Collaborate closely with architects, product teams, SMEs, and engineering partners to deliver scalable, resilient, and automated compensation processing systems.
8+ years of experience designing and implementing complex systems with at least 5 years in hands-on data engineering.
Strong proficiency in Python for ETL/ELT and pipeline orchestration and hands-on experience with AWS services including Glue, Lambda, EventBridge, RDS, and S3.
Strong SQL skills including stored procedures, indexing, and optimization; DevOps experience with GitHub, CI/CD, and deployment pipelines.
Bachelor's degree in Computer Science or related field.
Experienced in transformation-heavy or rules-driven domains preferably related to compensation, payroll, financial calculations, or similar systems.
Comfortable working in a fast-paced Agile environment with a focus on modernization and automation of legacy systems to cloud-native platforms.
Demonstrates strong ownership for delivering high-quality, scalable, and resilient cloud data engineering solutions with a collaborative approach involving cross-functional teams.