We are looking for experienced Data Engineers to join our data team. Your main goal is to build, maintain, and scale our data infrastructure that powers our payment analytics, fraud detection, compliance reporting, and business intelligence systems. You will be responsible for designing robust data pipelines, ensuring data quality, and enabling data-driven decision making across the organization.
Because of the sensitive nature of payment data and regulatory requirements, data security, privacy, and compliance are fundamental to everything we do. You will architect scalable data solutions that handle high-volume transaction data while maintaining the highest standards of security and performance that our payment platform demands.
Aside from your role and responsibilities, our entire team helps shape MoneyHash's company vision and culture. Our team members should always show:
Respect. We are a global team - we value the diversity of humanity and seek the good in people. We expect you to be empathetic and cultivate respectful relationships with others.
Humility: We welcome open discussion and candid feedback, and expect all candidates to arrive ego-free and with a commitment to better themselves and others.
Flexibility: Being comfortable with fast-paced working environments is a must. We seek a highly motivated self-starter that can quickly get up to speed and rise to any challenge.
Willingness to learn: We search for champions of learning with a growth mindset. Mistakes are celebrated and part of our road to success.
Design and build scalable data pipelines to process high-volume payment transaction data
Architect and maintain data warehouses and data lakes on AWS cloud infrastructure
Implement real-time and batch data processing systems for fraud detection and analytics
Develop ETL/ELT processes to integrate data from multiple payment gateways and third-party sources
Ensure data quality, consistency, and reliability across all data systems
Build and maintain data models for business intelligence and reporting needs
Implement data governance frameworks and ensure compliance with financial regulations
Collaborate with data scientists and analysts to enable advanced analytics and machine learning
Design and implement data security measures including encryption, access controls, and audit trails
Monitor data pipeline performance and optimize for cost and efficiency
Create comprehensive documentation for data architecture and pipeline processes
Work closely with backend engineers to implement data collection and instrumentation
Establish data monitoring and alerting systems to ensure pipeline reliability
Take ownership of data incidents and lead resolution efforts
Mentor junior team members and establish data engineering best practices
Support regulatory reporting requirements and compliance audits
Mid-Level (3-5 years) / Senior (5+ years) experience in data engineering roles
Strong experience building and maintaining large-scale data pipelines
Expertise in ETL/ELT processes and data integration patterns
Solid understanding of data modeling, warehousing, and analytics concepts
Proficiency in Python and/or Scala for data processing
Strong SQL skills and database optimization experience
Experience with data processing frameworks (Apache Spark, Apache Kafka, Apache Airflow)
Familiarity with streaming data technologies (Apache Kafka, AWS Kinesis, Apache Pulsar)
Knowledge of containerization for data pipelines (Docker, Kubernetes)
Understanding of CI/CD practices for data engineering projects
Knowledge of time-series databases for analytics (InfluxDB, TimescaleDB)
Understanding of database performance tuning and optimization
Experience in fintech, payment processing, or financial services industry
AWS certifications (Data Analytics, Solutions Architect, or Big Data)
Experience with real-time fraud detection and risk management systems
Knowledge of payment industry data standards and compliance requirements (PCI DSS, PSD2)
Familiarity with data visualization tools (Tableau, Power BI, Looker)
Experience with graph databases (Neo4j, Amazon Neptune) for fraud detection
Understanding of financial data analysis and payment metrics
Very competitive salary - stock options - health insurance - professional development stipend - wellness stipend
Originally posted on Himalayas
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