Senior Data Analytics / Data Engineer

Job Description

Job Title: Senior Data Analytics / Data Engineer Overview We are seeking a highly skilled Senior Data Analytics/Engineer with strong expertise in Python , Snowflake , Databricks , and SQL to design, build, and optimize our modern data platforms. The ideal candidate will have hands-on experience with DBT Core (highly preferred) and a solid understanding of CI/CD pipelines using GitHub Actions . This role will lead data engineering initiatives, drive best practices, and contribute to high-impact analytics projects across the organization. Key Responsibilities Design, develop, and maintain scalable data pipelines and workflows using Python , Snowflake , and Databricks . Build and automate ELT/ETL processes leveraging best practices in data modeling and transformation. Develop transformation models using DBT Core (preferred) to standardize and streamline data operations. Optimize large-scale datasets for performance, reliability, and accessibility. Write advanced, high-performance SQL queries for data extraction, transformation, and analysis. Implement and manage CI/CD workflows using GitHub Actions for automated testing, deployment, and version control. Collaborate with data analysts, data scientists, and business stakeholders to deliver high-quality data solutions. Ensure data integrity, security, and governance across platforms. Troubleshoot complex data issues and implement long-term automation and monitoring solutions. Stay current with emerging data engineering tools and best practices. Required Skills & Qualifications 5+ years of experience in Data Engineering or Senior Data Analytics roles. Strong proficiency in Python for data engineering and automation. Hands-on experience working with Snowflake and Databricks environments. Expert-level SQL skills and experience working with large datasets. Experience with DBT Core (highly preferred; strong advantage). Experience implementing CI/CD pipelines using GitHub Actions . Solid understanding of data warehousing, data modeling (e.g., Kimball, Data Vault), and ETL/ELT principles. Familiarity with cloud platforms such as AWS, Azure, or GCP. Strong problem-solving abilities and ability to work independently in a fast-paced environment. Preferred Qualifications Experience with infrastructure-as-code or automation tools. Knowledge of testing frameworks for data validation (e.g., Great Expectations). Experience working in an agile environment.