Data & ML Engineer

About the role

We're looking for a Data & ML Engineer to join our Digital Onboarding team. Your role will involve building and supporting data engineering, ETL, and MLOps capabilities that power Merchant Opportunity Analysis (MOA) and Offer Engine.

Responsibilities

• Build and maintain data pipelines that support MOA, Offer Engine, customer insights, personalization, and Digital Onboarding use cases.
• Develop ETL workflows using Python, SQL, AWS Glue, Qlik Data Integration, Snowflake, and related tools.
• Ingest, transform, validate, and deliver internal and external data sources.
• Support feature preparation, scoring workflows, model output processing, and ML integration patterns.
• Implement data quality checks, error handling, reconciliation logic, and pipeline monitoring.
• Collaborate with data scientists to understand feature needs and help prepare datasets for modeling and production use.
• Support integration of model outputs, recommendation data, and customer insights into Digital Onboarding applications.
• Troubleshoot data pipeline issues, production defects, and integration failures.

Requirements

• 4+ years of experience in data engineering, ETL development, ML engineering, analytics engineering, or software engineering.
• Hands-on experience with Python, SQL, and data pipeline development.
• Experience working with data integration or ETL tools such as AWS Glue, Qlik Data Integration, Snowflake, or similar platforms.
• Familiarity with AWS services such as S3, Glue, Lambda, SageMaker, CloudWatch, or related cloud services.
• Understanding of data modeling, data quality, orchestration, metadata, and pipeline monitoring.
• Exposure to machine learning workflows, feature engineering, batch scoring, or model deployment support.
• Experience with structured and semi-structured data.
• Familiarity with Git, CI/CD pipelines, automated testing, and Agile delivery practices.
• Strong problem-solving skills and ability to troubleshoot pipeline and data issues.
• Able to collaborate effectively with engineering, data science, product, and business teams.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Information Systems, or a related field (or equivalent industry experience).
• Experience supporting offer optimization, personalization, recommendation, customer insights, onboarding, or digital acquisition platforms.
• Exposure to MLOps practices, model registries, feature stores, batch scoring, or model monitoring.
• Experience with CDC, event-driven integration, or near-real-time data movement.
• Experience working with merchant, customer, application, product, or transaction data.
• Experience in financial services, fintech, merchant services, payments, or digital commerce.
• Experience using AI-assisted development tools or Agentic SDLC practices.
• AWS Data Analytics, Cloud Practitioner, or related certifications.