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.
