Data Engineer Full-time (Apache Spark, Python)

Data Engineer – Glendale, CA (Relocation Available)
Location: Glendale, California (Onsite/Hybrid as per client requirement)
Interview Process: 3 Rounds
Relocation Assistance: Available

Role Overview

As a Data Engineer you will play a key role in building and maintaining scalable data platforms and pipelines that enable data-driven decision-making across the organization. You will work with modern cloud and big data technologies including Airflow, Spark, Databricks, Delta Lake, Kubernetes, and AWS.

Key Responsibilities

• Maintain, enhance, and expand existing Core Data platform pipelines.
• Build tools and services supporting data discovery, lineage, governance, and privacy.
• Design, develop, and optimize scalable data solutions.
• Collaborate with Data Engineers, Software Engineers, Product Managers, Architects, and cross-functional teams.
• Develop and document standards, best practices, and governance frameworks.
• Ensure platform reliability, performance, data quality, and SLA compliance.
• Participate actively in Agile/Scrum ceremonies and team initiatives.
• Support stakeholders across Engineering, Analytics, Data Science, and Operations teams.
• Maintain detailed technical and operational documentation.

Required Skills & Experience

• 3+ years of experience building and supporting production data pipelines.
• Hands-on experience with Apache Spark and Airflow in production environments.
• Strong proficiency in Python, Java, or Scala (Python preferred).
• Advanced SQL skills and experience working with complex datasets.
• Hands-on experience with Databricks.
• Experience with Snowflake Data Warehouse.
• Strong AWS cloud experience (Infrastructure as Code experience is a plus).
• Understanding of Data Modeling, Data Warehousing, OLTP, and OLAP concepts.
• Experience with Agile/Scrum methodologies.
• Bachelor's degree in Computer Science, Information Systems, or equivalent experience.