Data Engineer

Data Engineer (DBT, Snowflake, Python)

8-10 Years

USA

We are looking for a skilled Data Engineer with strong hands-on experience in building scalable and efficient data pipelines. The ideal candidate will have deep expertise in DBT, Snowflake, and Python, and a solid understanding of modern data engineering practices. Candidate must have relevant experience of 8-10 Years. You will be responsible for designing, developing, and optimizing data pipelines and transformation workflows to support analytics, reporting, and business intelligence needs.

• Design, develop, and maintain scalable data pipelines using DBT, Snowflake, and Python.
• Build and manage data transformation workflows using DBT (models, macros, testing, and documentation).
• Develop efficient data ingestion and processing pipelines using Python.
• Optimize Snowflake data models, queries, and performance for large-scale datasets.
• Ensure data quality, reliability, and consistency through testing and validation frameworks.
• Collaborate with data analysts, business teams, and stakeholders to understand data requirements.
• Implement best practices for data modeling, version control, and pipeline orchestration.
• Monitor and troubleshoot data pipeline issues and performance bottlenecks.
• Maintain clear and structured documentation for data workflows and pipelines.
• Deliver robust and scalable data pipelines that support analytics and reporting needs.
• Develop and maintain DBT-based transformation frameworks to standardize data transformations.
• Produce optimized Snowflake data models and queries for high-performance analytics.
• Ensure delivery of high-quality, reliable datasets for analytics and reporting.

• Ability to work effectively as a contractor in a cross-functional environment with data analysts, engineers, and business stakeholders.
• Strong problem-solving and analytical mindset with attention to detail and data quality.
• Capability to work on enterprise-scale data platforms and support complex data ecosystems.
• Adaptability to evolving data engineering tools, frameworks, and best practices.
• Good communication skills to explain technical concepts to non-technical stakeholders.

• 8-10 years of hands-on experience in Data Engineering, with a focus on building scalable data pipelines.
• Strong expertise in DBT (Data Build Tool), including models, macros, testing, and documentation.
• Solid experience with Snowflake, including data warehousing, performance tuning, and optimization.
• Strong expertise in Python for data processing and pipeline development.
• Good understanding of SQL and data modeling concepts (star schema, dimensional modeling).
• Experience with data pipeline orchestration tools (such as Airflow or similar).
• Familiarity with data quality and testing frameworks to ensure reliable datasets.
• Strong problem-solving and analytical skills for diagnosing and resolving data issues.
• Experience working in cloud environments (AWS, Azure, or GCP).
• Familiarity with CI/CD practices for data pipelines and automated deployments.
• Exposure to real-time or streaming data pipelines is a plus.
• Experience in enterprise-scale data platforms and large-scale data environments.
• Background or familiarity with Data Automation & AI, Data Engineering, Data Analytics, and Databricks or similar modern data platforms is an advantage.