Published on: 2025-02-14 | US , GA - Atlanta - GA - Atlanta | Position Type: 4 | Job ID: 25-60661
- Analyze large and complex datasets to identify trends, insights, and business opportunities within the payment domain.
- Develop, optimize, and maintain data pipelines to support business intelligence and analytics.
- Work extensively with Aurora DB (MySQL/PostgreSQL) for data modeling, querying, and performance tuning.
- Design and implement scalable data architectures, ensuring data integrity and security.
- Collaborate with data analysts, software engineers, and business teams to define data-driven solutions.
- Implement machine learning models to enhance fraud detection, transaction analytics, and customer behavior analysis.
- Automate data ingestion, transformation, and storage processes using ETL frameworks.
- Utilize cloud platforms (AWS, GCP, or Azure) for data engineering and storage solutions.
- Monitor data quality, identify anomalies, and improve data accuracy.
- Stay updated on industry trends, particularly in payments domains, fintech, and emerging data technologies.
Required Skills:
- 3-6 years of experience as a Data Engineer/Data Scientist, preferably in the payment domain industry.
- Strong expertise in Aurora DB (MySQL/PostgreSQL) schema design, indexing, query optimization, and performance tuning.
- Proficiency in SQL and database management.
- Hands-on experience with Python, R, or Scala for data processing and analysis.
- Experience with ETL frameworks and data pipeline development.
- Familiarity with Big Data technologies (e.g., Spark, Hadoop, Kafka) is a plus.
- Cloud experience in AWS, GCP, or Azure, particularly in data storage and processing.
- Strong analytical and problem-solving skills with experience in predictive modeling and statistical analysis.
- Knowledge of fraud detection, transaction processing, or risk analytics in payments is highly desirable.
- Experience working with data visualization tools (e.g., Tableau, Power BI) is a plus.
- Ability to communicate insights and recommendations to stakeholders effectively.
Preferred:
- Certifications in AWS Data Engineering, Big Data, or Machine Learning are a plus.
