Data Engineer [Mid-Level & Senior] [Remote]

What we're looking for 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. What you will be doing 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 Requirements Core Data Engineering Skills 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 Preferred Qualifications 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 Compensation Package Very competitive salary - stock options - health insurance - professional development stipend - wellness stipend Originally posted on Himalayas