Senior Data Engineer
1 week ago
We are seeking an experienced Data Architect to design and implement scalable, high-performance data pipelines using Snowflake and dbt. The ideal candidate will have a strong understanding of modern data warehousing principles and experience working with cloud-based data platforms.
The successful candidate will lead the development of modular, test-driven ELT pipelines using dbt on Snowflake, define architectural best practices, and drive data transformation at scale. They will work closely with clients to translate business needs into robust data solutions and play a key role in mentoring junior engineers, enforcing standards, and delivering production-grade data platforms.
This is a challenging opportunity for a skilled Data Engineer looking to take their career to the next level. The ideal candidate will be comfortable working in a fast-paced environment and have excellent communication and problem-solving skills.
Key Responsibilities:
">- Architect and Implement Modular Data Pipelines: Design and develop scalable, high-performance data pipelines using Snowflake and dbt.
- Define Architectural Best Practices: Establish and enforce best practices for data architecture, including data modeling, data governance, and data security.
- Drive Data Transformation at Scale: Lead the development of data transformations to meet business needs, while ensuring data quality and integrity.
- Mentor Junior Engineers: Provide guidance and support to junior engineers to help them develop their skills and knowledge.
- Deliver Production-Grade Data Platforms: Collaborate with clients to deliver high-quality data platforms that meet their needs and exceed their expectations.
Required Skills and Qualifications:
">- 5+ Years of Experience in Data Engineering: Proven experience in designing and developing data pipelines, data architectures, and data governance frameworks.
- Expert-Level Knowledge of SQL and Snowflake: Strong understanding of SQL and Snowflake, including performance optimization, storage layers, query profiling, clustering, and cost management.
- Experience with dbt Development: Experience in developing modular model designs, macros, tests, documentation, and version control using Git.
- Cloud-Based Data Platforms: Experience working with cloud-based data platforms, including Snowflake, AWS S3, Azure Data Lake, and Google Cloud Storage.
- Modern Data Warehousing Principles: Strong understanding of modern data warehousing principles, including dimensional modeling, slowly changing dimensions, and fact tables.
Benefits:
">- Opportunity to Work with a Fast-Paced Team: Join a dynamic team of data professionals who are passionate about delivering high-quality data solutions.
- Competitive Salary and Benefits Package: Receive a competitive salary and benefits package, including health insurance, retirement savings plan, and paid time off.
- Professional Development Opportunities: Participate in training and development programs to enhance your skills and knowledge.
How to Apply:
">- Review the Job Description: Carefully review the job description to ensure you meet the required qualifications and have the necessary skills and experience.
- Submit Your Application: Submit your application, including your resume, cover letter, and any relevant certifications or references.
- Participate in Interviews: Participate in interviews with our team to discuss your qualifications and fit for the role.
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