Full Stack Software Engineer - Hybrid

Overview You design scalable data systems and pipelines to enable advanced analytics and ML workflows. In this hybrid role, you focus on building robust data pipelines, with strong data modeling and Python-based processing underpinning the platform. You collaborate with data scientists and engineers to support model training and deployment at scale. This position offers impact by delivering production-grade data foundations that power AI initiatives and high-throughput data environments. Compensation / Benefitsbase salary and compensation transparencyAxcelis Team Incentive bonus plancomprehensive benefits packagehybrid work arrangementcareer growth opportunities ResponsibilitiesDesign and build end-to-end data pipelines (ETL/ELT) for ingesting, processing, and transforming data from multiple sources, including logs and JSON data, with full data traceability and quality controls.Design and manage scalable database schemas for both single-node and distributed environments, including partitioning and sharding strategies and query optimization.Develop Python-based data processing workflows using dataframes (Pandas, NumPy) and visualize/analyze with Plotly or similar; automate workflows and integrate into pipelines.Prepare and transform datasets for ML models; collaborate with data scientists to support model training and production deployment and enable scalable ML data foundations. Key requirementsBachelor’s or Master’s degree in Computer Science or Engineering and 5+ years of experienceStrong experience in database design and SQL-based systemsHands-on experience with distributed systems, partitioning, and shardingProven experience building data pipelines (ETL/ELT)Strong proficiency in Python for data processingExperience with log-based and semi-structured data (JSON)Understanding of data traceability, validation, and governanceproblem-solvingcollaborationclear communicationPythonPandasNumPy