Senior Data Engineer

Description:

Global Applications Solution is actively hiring a Senior Data Engineer for a full-time, onsite position located in either Sunnyvale, CA or Dallas, TX. This opportunity is ideal for a highly seasoned data professional with at least 12 years of experience in data engineering, including deep expertise in Snowflake and Python. Candidates must also have a LinkedIn profile created before 2019, indicating a well-established professional presence.

The role demands comprehensive experience in designing and optimizing large-scale data pipelines, a strong foundation in data architecture, and a demonstrated ability to deliver robust, scalable data solutions in collaboration with cross-functional teams.

Key Responsibilities:

• Architect, design, and optimize scalable ETL/ELT data pipelines using Snowflake.

• Develop clean, efficient, and scalable Python code for data integration, transformation, and automation.

• Engage with stakeholders and business units to gather and interpret data requirements.

• Monitor and maintain pipeline stability and performance, ensuring timely and accurate data delivery.

• Implement robust data quality frameworks and automate detection/resolution processes.

• Collaborate with DevOps and cloud infrastructure teams for deployment and operational support.

Required Qualifications:

• 12+ years of hands-on experience in data engineering.

• Deep expertise in Snowflake: development, optimization, and administration.

• Advanced proficiency in Python for data workflows and transformation logic.

• Solid knowledge of cloud data platforms, data modeling, and data warehousing best practices.

• Strong grasp of performance tuning, data security, and governance standards.

• LinkedIn profile must be created before 2019.

• Must be able to work 100% onsite at either Sunnyvale, CA or Dallas, TX (remote/hybrid work is not permitted).

Nice to Have Skills:

• Experience with orchestration tools like Apache Airflow or Prefect.

• Familiarity with CI/CD pipelines and automated data deployment strategies.

• Exposure to other cloud data platforms such as Databricks, AWS Redshift, or Google BigQuery