Software Engineer — Data Engineering

Salary: $42,000 - $54,000 per year Location : , International Employment option: Job type: Full time Job Summary: We are looking for a strong Software Engineer with experience in data engineering to join an international team working on large-scale solutions in the financial domain. This role involves building robust, scalable, and maintainable data pipelines and services in a cloud-based environment. You’ll be part of a cross-functional, high-performance team working with real-time and high-volume data systems. Skills Must Have Hard skills: - novice in: JAVA - beginner in: Pipeline, Data Pipelines, ETL - competent in: Data Engineering, SQL Soft skills: - competent in: Communication Skills Nice-to-have Hard skills: - beginner in: Performance Optimization, Logic, Prometheus, FinTech, Apache, Kubernetes, Microsoft Clarity, Microservices, Software Engineering, Redis, ClickHouse, Trading, OOD, Snowflake, Airflow, Kafka, RDBMS, Grafana, SOLID, Fraud Detection, Monitoring, Data Storage, Datadog, Accountability Job Description Additional Requirements 3+ years of experience with Java (in production environments) 3+ years in data engineering and pipeline development with large volumes of data Experience with ETL workflows and data processing using cloud-native tools Strong knowledge of SQL, relational and non-relational databases, and performance optimization Experience with monitoring tools (e.g., Prometheus, Grafana, Datadog) Familiarity with Kubernetes, Kafka, Redis, Snowflake, Clickhouse, Apache Airflow Solid understanding of software engineering principles and object-oriented design Ability to work independently and proactively, with strong communication skills Responsibilities Design and develop microservices for the data engineering team (Java-based, running on Kubernetes) Build and maintain high-performance ETL workflows and data ingestion logic Handle data velocity, duplication, schema validation/versioning, and availability Integrate third-party data sources to enrich financial data Collaborate with cross-functional teams to align data consumption formats and standards Optimize data storage, queries, and delivery for internal and external consumers Maintain observability and monitoring across services and pipelines About Company