Description: About Solidus Labs At Solidus, we are shaping the financial markets of tomorrow by providing cutting-edge trade surveillance technology that protects investors, enhances transparency, and ensures regulatory compliance across traditional financial assets, prediction and crypto markets. With over 20 years of experience in developing Wall Street-grade FinTech, our team delivers innovative solutions that financial institutions and regulators worldwide rely on to detect, investigate, and report market manipulation, financial crime, and fraud. Headquartered in Wall Street, with offices in Singapore, Tel Aviv, and London, we safeguard millions of retail and institutional entities globally, monitoring over a trillion events each day. The Role We’re looking for a strong Software Engineer with Data Engineering experience. Someone who is proficient in building robust, scalable, maintainable and thoroughly monitored data pipelines on cloud environments. As an ambitious start-up in an extremely dynamic space, we pride ourselves on being independent, accountable, and organized, have a self-starter attitude, and be willing to get their hands dirty with day-to-day work that might be out of their official scope, while keeping an eye on their goals and the big picture. Responsibilities: Design and implement customer facing integrations of various asset types into the data pipelines Design and develop the data's team micro services - Java services running on K8S and in AWS. Develop, design, and maintain end-to-end ETL workflows, including data ingestion and transformation logic, involving different data sources. Enrich financial data through third-party data integrations, FIX, CSV, JSON and other formats - including market (e.g. order book) and reference (e.g. company information) data. AI-first solution approach. Coding using AI agents, such as Claude, for a given problem context, with adherence to the architectural and coding conventions of the organization Plan and communicate integrations with other teams that consume the data and use it for insights creation. Strong collaboration with product and customer facing teams Tackle data duplication, velocity, schema adherence (and schema versioning), high availability, data governance, and more. Requirements: BSc. in Computer Sciences. Strong background as a software engineer with at least 3+ years experience with Java. 5+ years in data engineering, and data pipeline development on high-volume, low-latency production environments. Experience working in fintech, crypto or trading industries, and familiarity with FIX and market data is an advantage. Experience with monitoring systems (Prometheus, Grafana). Experience with data-engineering cloud technologies as Apache Airflow, K8S, Clickhouse, Snowflake, Redis, Caching technologies and Kafka. Proven experience with relational,non-relational, and time series DBs. Proficient in SQL and query optimizations. Experience with designing infrastructure at scale to maintain high availability SLAs. Experience with monitoring and managing production environments. Curiosity, ability to work independently and proactively identify solutions. Strong communication skills. Excellent verbal and written communication skills in a remote environment, working cross functionally Responsibilities null Requirements null Benefits null