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In this role, you will be responsible for building scalable data pipelines, ensuring data integrity, and integrating third-party data sources. Your primary focus will be to enable efficient data flow and support analytical capabilities across the organization. You will also contribute to the development of our data architecture, implement best engineering practices, and collaborate closely with cross-functional teams to turn raw data into actionable insights.\nResponsibilities\nCommunicate with technical and non-technical stakeholders to gather and clarify business requirements\nReview and analyze data and business logic to ensure consistency, accuracy, and reliability\nDesign, implement, and maintain data pipelines for efficient and scalable data processing\nIntegrate, maintain, and support data solutions and third-party data sources\nResearch and evaluate third-party tools, services, and components for potential use\nFollow engineering best practices, including code reviews, testing, refactoring, and continuous delivery\nDesign, optimize, and maintain data storage solutions\nRequirements\n3+ years of commercial experience in Data Engineering\nExperience gathering business requirements and communicating with stakeholders\nStrong knowledge of Data Warehouse (DWH) architecture and principles\nHands-on experience designing data warehouses and building ETL pipelines\nDeep practical experience with Python\nHands-on experience in one or more of the following areas: data processing using PySpark, Apache Spark, Pandas, or similar frameworks; data scraping; integration of third-party data sources and APIs\nProficiency in SQL and relational databases such as PostgreSQL and MySQL\nHands-on experience with column-oriented databases such ClickHouse, Snowflake, Cassandra, BigQuery (many tables with millions of records and above each)\nSolid understanding of software design patterns, algorithms, and data structures\nIntermediate English proficiency\nWill be a plus\nExperience with messaging platforms such as RabbitMQ or Kafka\nFamiliarity with DataOps practices and data pipeline automation\nFamiliarity with CI/CD pipelines and Kubernetes environments\nBackground in FinTech or Trading domains\nWe offer\nTax expenses coverage for 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