

aKUBE
Senior Data Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Engineer in Glendale, CA, offering a 12-month contract at up to $85/hr. Key requirements include 5+ years of data engineering experience, proficiency in Airflow, Spark, Databricks, SQL, and AWS, with strong programming skills in Python, Java, or Scala.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
680
-
ποΈ - Date
December 6, 2025
π - Duration
More than 6 months
-
ποΈ - Location
Hybrid
-
π - Contract
W2 Contractor
-
π - Security
Unknown
-
π - Location detailed
Glendale, CA
-
π§ - Skills detailed
#Kubernetes #Python #GraphQL #SQL (Structured Query Language) #Airflow #Databricks #Scrum #Programming #Datasets #Delta Lake #Scala #Agile #Data Modeling #AWS (Amazon Web Services) #Spark (Apache Spark) #Documentation #API (Application Programming Interface) #Data Quality #Data Engineering #Java
Role description
City: Glendale, CA
Onsite/ Hybrid/ Remote: Hybrid (3 days a week onsite, Friday - Remote)
Duration: 12 months
Rate Range: Up to$85/hr on W2 depending on experience (no C2C or 1099 or sub-contract)
Work Authorization: GC, USC, All valid EADs except OPT, CPT, H1B
Must Have:
β’ 5+ years Data Engineering
β’ Airflow
β’ Spark DataFrame API
β’ Databricks
β’ SQL
β’ API integration
β’ AWS
β’ Python or Java or Scala
Responsibilities:
β’ Maintain, update, and expand Core Data platform pipelines.
β’ Build tools for data discovery, lineage, governance, and privacy.
β’ Partner with engineering and cross-functional teams to deliver scalable solutions.
β’ Use Airflow, Spark, Databricks, Delta Lake, Kubernetes, and AWS to build and optimize workflows.
β’ Support platform standards, best practices, and documentation.
β’ Ensure data quality, reliability, and SLA adherence across datasets.
β’ Participate in Agile ceremonies and continuous process improvement.
β’ Work with internal customers to understand needs and prioritize enhancements.
β’ Maintain detailed documentation that supports governance and quality.
Qualifications:
β’ 5+ years in data engineering with large-scale pipelines.
β’ Strong SQL and one major programming language (Python, Java, or Scala).
β’ Production experience with Spark and Databricks.
β’ Experience ingesting and interacting with API data sources.
β’ Hands-on Airflow orchestration experience.
β’ Experience developing APIs with GraphQL.
β’ Strong AWS knowledge and infrastructure-as-code familiarity.
β’ Understanding of OLTP vs OLAP, data modeling, and data warehousing.
β’ Strong problem-solving and algorithmic skills.
β’ Clear written and verbal communication.
β’ Agile/Scrum experience.
β’ Bachelorβs degree in a STEM field or equivalent industry experience.
City: Glendale, CA
Onsite/ Hybrid/ Remote: Hybrid (3 days a week onsite, Friday - Remote)
Duration: 12 months
Rate Range: Up to$85/hr on W2 depending on experience (no C2C or 1099 or sub-contract)
Work Authorization: GC, USC, All valid EADs except OPT, CPT, H1B
Must Have:
β’ 5+ years Data Engineering
β’ Airflow
β’ Spark DataFrame API
β’ Databricks
β’ SQL
β’ API integration
β’ AWS
β’ Python or Java or Scala
Responsibilities:
β’ Maintain, update, and expand Core Data platform pipelines.
β’ Build tools for data discovery, lineage, governance, and privacy.
β’ Partner with engineering and cross-functional teams to deliver scalable solutions.
β’ Use Airflow, Spark, Databricks, Delta Lake, Kubernetes, and AWS to build and optimize workflows.
β’ Support platform standards, best practices, and documentation.
β’ Ensure data quality, reliability, and SLA adherence across datasets.
β’ Participate in Agile ceremonies and continuous process improvement.
β’ Work with internal customers to understand needs and prioritize enhancements.
β’ Maintain detailed documentation that supports governance and quality.
Qualifications:
β’ 5+ years in data engineering with large-scale pipelines.
β’ Strong SQL and one major programming language (Python, Java, or Scala).
β’ Production experience with Spark and Databricks.
β’ Experience ingesting and interacting with API data sources.
β’ Hands-on Airflow orchestration experience.
β’ Experience developing APIs with GraphQL.
β’ Strong AWS knowledge and infrastructure-as-code familiarity.
β’ Understanding of OLTP vs OLAP, data modeling, and data warehousing.
β’ Strong problem-solving and algorithmic skills.
β’ Clear written and verbal communication.
β’ Agile/Scrum experience.
β’ Bachelorβs degree in a STEM field or equivalent industry experience.






