

Extend Information Systems Inc.
Big Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Big Data Engineer in Phoenix, AZ (Hybrid) for a contract length of unspecified duration, offering competitive pay. Requires 7+ years in Big Data, expertise in Hadoop, Spark, GCP, and proficiency in Python/Scala/Java.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 29, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Phoenix, AZ
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🧠 - Skills detailed
#Scala #Deployment #Data Pipeline #Big Data #Data Quality #SQL (Structured Query Language) #Terraform #Cloud #Dataflow #Docker #Airflow #Storage #Pig #Spark (Apache Spark) #Python #GCP (Google Cloud Platform) #Kubernetes #Kafka (Apache Kafka) #Data Governance #Data Science #Data Engineering #Sqoop (Apache Sqoop) #Data Cleansing #Security #BigQuery #Java #"ETL (Extract #Transform #Load)" #HDFS (Hadoop Distributed File System) #Data Processing #Hadoop #GIT #Apache Spark
Role description
Job Title: Big Data Engineer
Job Location: Phoenix, AZ (Hybrid)
Job Description
We are seeking an experienced Big Data Engineer with strong expertise in Hadoop, Spark, and Google Cloud Platform (GCP). The ideal candidate will design, develop, and optimise large-scale data processing pipelines and analytical solutions on the cloud.
Responsibilities:
• Design and implement data pipelines and ETL processes using Spark, Hadoop, and GCP services (BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage).
• Work with structured and unstructured data from multiple sources and perform data cleansing, transformation, and aggregation.
• Collaborate with data scientists, analysts, and application teams to deliver scalable data solutions.
• Optimise data performance and ensure reliability, availability, and scalability of data systems.
• Implement data governance, quality, and security best practices.
• Troubleshoot performance and data quality issues in distributed systems.
Required Skills:
• 7+ years of experience in Big Data technologies.
• Strong hands-on experience with Hadoop ecosystem (HDFS, Hive, Pig, Sqoop, Oozie).
• Expertise in Apache Spark (Core, SQL, Streaming).
• Strong experience with GCP data services – BigQuery, Dataflow, Dataproc, Composer, Cloud Storage, Pub/Sub.
• Proficiency in Python/Scala/Java for data processing.
• Good knowledge of SQL and data modelling concepts.
• Familiarity with CI/CD, Git, and Cloud Deployment tools.
Nice to Have:
• Experience with Airflow, Terraform, or Dataform.
• Knowledge of Kafka or real-time streaming.
• Familiarity with Docker/Kubernetes.
Job Title: Big Data Engineer
Job Location: Phoenix, AZ (Hybrid)
Job Description
We are seeking an experienced Big Data Engineer with strong expertise in Hadoop, Spark, and Google Cloud Platform (GCP). The ideal candidate will design, develop, and optimise large-scale data processing pipelines and analytical solutions on the cloud.
Responsibilities:
• Design and implement data pipelines and ETL processes using Spark, Hadoop, and GCP services (BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage).
• Work with structured and unstructured data from multiple sources and perform data cleansing, transformation, and aggregation.
• Collaborate with data scientists, analysts, and application teams to deliver scalable data solutions.
• Optimise data performance and ensure reliability, availability, and scalability of data systems.
• Implement data governance, quality, and security best practices.
• Troubleshoot performance and data quality issues in distributed systems.
Required Skills:
• 7+ years of experience in Big Data technologies.
• Strong hands-on experience with Hadoop ecosystem (HDFS, Hive, Pig, Sqoop, Oozie).
• Expertise in Apache Spark (Core, SQL, Streaming).
• Strong experience with GCP data services – BigQuery, Dataflow, Dataproc, Composer, Cloud Storage, Pub/Sub.
• Proficiency in Python/Scala/Java for data processing.
• Good knowledge of SQL and data modelling concepts.
• Familiarity with CI/CD, Git, and Cloud Deployment tools.
Nice to Have:
• Experience with Airflow, Terraform, or Dataform.
• Knowledge of Kafka or real-time streaming.
• Familiarity with Docker/Kubernetes.






