Senior Data Engineer

Functions - Design, develop, and maintain scalable data pipelines using Databricks and Apache Spark. - Define data architectures that support batch and streaming processing. - Integrate data from multiple sources, including databases, APIs, and cloud storage. - Optimize data solutions for performance, reliability, and cost efficiency. - Collaborate closely with data science, analytics, and business teams. - Provide technical leadership and guidance on data engineering best practices. - Translate complex Databricks architectures and data solutions into clear, business-friendly explanations for technical and non-technical audiences. - Document data architectures, pipelines, and technical decisions. - Support production systems and troubleshoot data-related issues as needed. Requirements - Minimum of 5 years of experience as a Data Engineer or in a similar role. - Strong hands-on experience with Databricks and Apache Spark. - Advanced SQL and Python skills. - Experience working in cloud environments (Azure preferred). - Solid understanding of data modeling, ETL/ELT processes, and data architecture concepts. - Experience designing enterprise-scale data platforms and building production-grade data pipelines. - Exposure to analytics, BI, or data science workloads. - Familiarity with CI/CD practices for data engineering. - Strong communication skills with both technical and non-technical stakeholders. - Any certifications for Databricks or Apache are a plus. Benefits - Competitive salary - Flexible work environment - Opportunities for growth and certifications - Inclusive and collaborative team culture - Access to cutting-edge tools and technologies