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

What we're looking forWe 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 doingDesign and build scalable data pipelines to process high-volume payment transaction dataArchitect and maintain data warehouses and data lakes on AWS cloud infrastructureImplement real-time and batch data processing systems for fraud detection and analyticsDevelop ETL/ELT processes to integrate data from multiple payment gateways and third-party sourcesEnsure data quality, consistency, and reliability across all data systemsBuild and maintain data models for business intelligence and reporting needsImplement data governance frameworks and ensure compliance with financial regulationsCollaborate with data scientists and analysts to enable advanced analytics and machine learningDesign and implement data security measures including encryption, access controls, and audit trailsMonitor data pipeline performance and optimize for cost and efficiencyCreate comprehensive documentation for data architecture and pipeline processesWork closely with backend engineers to implement data collection and instrumentationEstablish data monitoring and alerting systems to ensure pipeline reliabilityTake ownership of data incidents and lead resolution effortsMentor junior team members and establish data engineering best practicesSupport regulatory reporting requirements and compliance auditsRequirementsCore Data Engineering SkillsMid-Level (3-5 years) / Senior (5+ years) experience in data engineering rolesStrong experience building and maintaining large-scale data pipelinesExpertise in ETL/ELT processes and data integration patternsSolid understanding of data modeling, warehousing, and analytics conceptsProficiency in Python and/or Scala for data processingStrong SQL skills and database optimization experienceExperience 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 projectsKnowledge of time-series databases for analytics (InfluxDB, TimescaleDB)Understanding of database performance tuning and optimizationPreferred QualificationsExperience in fintech, payment processing, or financial services industryAWS certifications (Data Analytics, Solutions Architect, or Big Data)Experience with real-time fraud detection and risk management systemsKnowledge 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 detectionUnderstanding of financial data analysis and payment metricsCompensation Package Very competitive salary - stock options - health insurance - professional development stipend - wellness stipendOriginally posted on Himalayas Apply tot his job