We are looking for an experienced Data Engineer to jcreate and enhance dependable data platforms that support HR and enterprise analytics, partnering closely with analysts, engineering leads, and business stakeholders on site. The position focuses on building scalable pipelines, strengthening data quality, and enabling trusted insights that improve operational decision-making across the organization.

Responsibilities:

• Design, develop, and maintain scalable data pipelines that integrate information from files, APIs, databases, replicated sources, and streaming inputs.
• Build and support modern data environments across warehouses, data lakes, and lakehouse architectures to meet analytics and reporting needs.
• Partner with business analysts, HR stakeholders, and technical team members to translate data requirements into reliable engineering solutions.
• Improve data quality, lineage, and governance by applying metadata-driven practices and implementing controls that increase trust in enterprise datasets.
• Lead end-to-end delivery of data engineering initiatives, from solution design and development through testing, deployment, and operational support.
• Manage orchestration, scheduling, and monitoring of data workflows to ensure stable performance and timely delivery of critical datasets.
• Apply DevOps practices such as version control, automated testing, and CI/CD processes to increase deployment quality and team collaboration.
• Use Python, SQL, and cloud-based tools to automate data processing, optimize performance, and support scalable distributed workloads.
• Implement data protection measures, including masking, encryption, anonymization, and role-aware access design, especially for sensitive workforce information.
• Support curated analytical datasets and reporting solutions by collaborating with downstream users on trusted models and enterprise data products.