Data Engineer

Role: Data Engineer

Location: Glendale, CA

Work Mode: Hybrid (4 days work from)

Duration: Full time

Job Description:

As a Data Engineer, you will help build and maintain data solutions that enable analytics, reporting, and business decision-making across the organization. Working alongside data engineers, architects, product managers, and data consumers, you will develop reliable data pipelines, support data modeling efforts, and contribute to a scalable and efficient data platform. This role offers an opportunity to grow your technical expertise while working with modern cloud data technologies in a collaborative environment.

Key Responsibilities:

• Develop and maintain data platform pipelines and data integration processes.
• Support the implementation of conceptual, logical, and physical data models.
• Build and maintain data transformations using dbt and contribute to scalable, reliable data solutions.
• Collaborate with data engineers, data scientists, analysts, and cross-functional teams to deliver data products.
• Apply data engineering concepts and technologies, including AWS services (S3, Lambda, SNS, SQS), Iceberg, Snowflake, dbt, and Airflow.
• Participate in Agile/Scrum ceremonies and contribute to team planning and continuous improvement efforts.
• Work with product managers, architects, and engineers to support the Core Data Platform roadmap.
• Follow established standards and best practices for data pipelines, naming conventions, and platform development.
• Monitor and support the quality, reliability, and operational health of data platform datasets and pipelines.
• Contribute to documentation of data assets, processes, and platform standards.
• Partner with stakeholders to understand business requirements and support delivery of data solutions.
• Maintain documentation to support data quality, governance, and operational requirements.

Qualifications:

• 2–5 years of experience developing and supporting data pipelines.
• Understanding of data modeling concepts, including dimensional modeling and data normalization principles.
• Proficiency in at least one program