Senior Data Engineer

Work Schedule: Hybrid – 3 days onsite required OUT OF STATE CANDIDATES WILL AUTOMATICALLY BE REJECTED This is a full-time role; Client will not provide sponsorship. We are seeking a Technical Specialist, Data Engineering to join a strategic in‑house data platform build. This role will be a key contributor to the development of AxeoS’ internal data platform as the team shifts away from a previous vendor partnership and moves toward an open‑source, vendor‑neutral technology approach. The ideal candidate will bring strong hands‑on production experience across data movement, CDC, data modeling, ETL, and open‑source data technologies. This person should be comfortable working across the full solution, from infrastructure awareness to the data layer, and should be able to contribute both technical depth and a fresh industry perspective. Key Responsibilities Support the design and buildout of an internal data platform using open‑source and vendor‑neutral technologies. Move data from OLTP transactional systems into OLAP analytical environments. Design and support data models across both transactional and analytical databases. Implement and work with Change Data Capture processes and tools. Build and maintain ETL/data transformation workflows. Work with technologies such as Apache Iceberg, Debezium, Apache Flink, Apache Kafka, and AWS. Collaborate closely with internal product and engineering leads who bring deep AxeoS platform knowledge. Contribute to the overall architecture, scalability, and reliability of the data platform. Required Qualifications Hands‑on production experience moving data from OLTP systems to OLAP platforms. Practical experience with Change Data Capture concepts and tools. Strong understanding of Apache Iceberg, including table formats and OLAP data modeling. Solid data modeling experience across both OLTP and OLAP environments. End‑to‑end ETL and data transformation experience. Experience working with open‑source data tools such as Debezium, Apache Flink, and Apache Kafka. AWS experience, including the ability to deploy and manage data solutions with infrastructure awareness. Ability to understand and contribute across the full solution, from infrastructure to the data layer. Nice-to-Have Databricks experience, especially where it can bring efficiency to the platform. Financial services industry background. Python or PySpark familiarity; conceptual understanding is valued, though pure coding ability is not the main focus. #J-18808-Ljbffr