Senior Data Engineer

💻 Senior Data Engineer (Focus: Data Quality & Crypto Risk Platform)✨ About the RoleJoin the team behind Crypto Secure, a cutting-edge risk assessment platform that gives banks critical visibility into crypto spend, transaction volumes, and AML risk exposure. This is a high-impact, hybrid role requiring a dual focus: designing scalable data pipelines and implementing rigorous automated testing strategies to guarantee data integrity and trust.If you are passionate about applying your technical expertise to solve complex data challenges in the high-growth fintech and cryptocurrency space, we want to hear from you.📝 Role ResponsibilitiesData Engineering & Platform DevelopmentDesign and build robust, scalable ELT/ETL pipelines using Snowflake, Hadoop, Spark, NiFi, and other big data technologies.Write high-quality, maintainable code primarily in Python and SQL following best engineering practices.Implement data governance principles, metadata management, and lineage tracking into all data solutions.Optimize data architectures and workflows to handle massive, high-volume financial datasets efficiently.Data Quality Assurance & Testing (Crucial Focus)Develop and implement automated testing frameworks and validation scripts for all ETL processes and data transformations.Establish comprehensive data quality checks, reconciliation processes, and regression testing suites to ensure data accuracy, completeness, and timeliness.Perform unit, integration, and end-to-end testing for data pipelines and schema changes, utilizing tools like dbt tests and custom Python utilities.Contribute to CI/CD integration to embed quality and testing seamlessly into the deployment lifecycle.Collaboration & Agile DeliveryWork closely with Data Engineers, Product Managers, and Data Scientists to gather requirements and deliver data solutions.Actively participate in agile ceremonies (sprint planning, backlog refinement, retrospectives) with a strong emphasis on quality-first delivery.Support production incident response, providing rapid data validation and root cause analysis.🛠️ Skills & QualificationsRequired Technical Expertise (7-15 Years Overall Experience)Advanced SQL and deep experience with relational and NoSQL databases.Strong proficiency in Python for both data engineering and test automation.Hands-on experience with modern data platforms: Snowflake, Hadoop, Spark, Databricks, and Kafka.Proven experience in data testing methodologies, ETL validation, and developing automated data testing frameworks.Knowledge of data profiling, anomaly detection, and statistical validation techniques.Familiarity with workflow orchestration tools (e.g., Airflow).Required Professional AttributesStrong problem-solving, analytical skills, and attention to detail.Excellent communication skills for effective cross-functional collaboration.Ability to work independently and manage multiple priorities in a fast-paced, hybrid environment.