Sr Data Engineer

Pipe Recruit; Glendale (CA); On-site; USD 120,000 - 150,000; Full time

Job summary

A data solutions provider in Glendale is looking for an experienced Data Engineer to maintain and expand their core data platform. Responsibilities include building and maintaining APIs, collaborating with cross-functional teams, and ensuring high operational efficiency. Ideal candidates have over 7 years of experience developing large-scale data pipelines using tools like Airflow and Snowflake. This role is critical for delivering accurate data to support various teams, and applicants should be proficient in major programming languages like Python.

Qualifications

• 7+ years of data engineering experience developing large-scale data pipelines.
• Proficiency in at least one major programming language (Python, Java, or Scala).
• Hands-on experience with distributed processing systems such as Apache Spark.
• Production-level experience with data pipeline orchestration tools like Apache Airflow.
• Expertise in at least one MPP or cloud database technology (Snowflake, Databricks, BigQuery).
• Experience in data modeling and API development using GraphQL.
• Advanced understanding of OLTP vs. OLAP environments.

Responsibilities

• Maintain, update, and expand existing core data platform pipelines.
• Build and maintain APIs to expose data to downstream applications.
• Collaborate with product managers, architects, and other engineers to ensure platform success.
• Develop and document internal/external standards, best practices, and pipeline configurations.
• Ensure high operational efficiency and data accuracy to meet SLAs and reliability standards.

Skills

Data pipeline development

Python

Apache Spark

Data modeling

API development

Tools

Airflow

Databricks

Snowflake

Job description

• Maintain, update, and expand existing core data platform pipelines.
• Build and maintain APIs to expose data to downstream applications.
• Work with technologies including Airflow, Spark, Databricks, Delta Lake, and Snowflake.
• Collaborate with product managers, architects, and other engineers to ensure platform success.
• Develop and document internal/external standards, best practices, and pipeline configurations.
• Ensure high operational efficiency and data accuracy to meet SLAs and reliability standards for stakeholders (Engineering, Data Science, Operations, and Analytics teams).

Required Qualifications:

• 7+ years of data engineering experience developing large-scale data pipelines.
• Proficiency in at least one major programming language (Python, Java, or Scala).
• Hands‑on experience with distributed processing systems such as Apache Spark.
• Production‑level experience with data pipeline orchestration tools like Apache Airflow.
• Expertise in at least one Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Databricks, BigQuery).
• Experience in data modeling and API development using GraphQL.
• Advanced understanding of OLTP vs. OLAP environments.

Preferred Qualifications (Nice-to-Have):