Lorven Technologies Inc.
Java + Spark Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Java + Spark Data Engineer, offering a contract position in Phoenix, AZ or Rhode Island. Key skills include Java, Spark, data engineering, and cloud platforms (AWS, GCP, or Azure). Leadership experience and strong knowledge of the Hadoop ecosystem are required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
February 7, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Rhode Island, United States
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🧠 - Skills detailed
#Spark (Apache Spark) #Data Engineering #Airflow #Apache Spark #AWS (Amazon Web Services) #Data Processing #Cloud #Data Pipeline #Azure #Kafka (Apache Kafka) #Hadoop #GCP (Google Cloud Platform) #Java #Data Orchestration #Data Modeling #SQL (Structured Query Language)
Role description
Position: Java + Spark Data Engineer
Location: Phoenix, AZ or Rhode Island
Contract
Must Skills: Data, Spark, Java, Java Coding.
Job description:
• Java + Spark Data Engineer (Lead) with strong data engineering expertise and hands-on coding experience in Java using Spark frameworks.
• The candidate will design, build, and optimize large-scale data pipelines for processing structured and unstructured data.
• They will lead and mentor a team of 4–5 data engineers, ensuring best practices and timely delivery.
• The role requires deep knowledge of Apache Spark, Hadoop ecosystem, Hive, and distributed data processing.
• Experience with SQL, data modeling, and cloud platforms such as AWS, GCP, or Azure is essential.
• Familiarity with Kafka, Airflow, and modern data orchestration tools is an added advantage.
Position: Java + Spark Data Engineer
Location: Phoenix, AZ or Rhode Island
Contract
Must Skills: Data, Spark, Java, Java Coding.
Job description:
• Java + Spark Data Engineer (Lead) with strong data engineering expertise and hands-on coding experience in Java using Spark frameworks.
• The candidate will design, build, and optimize large-scale data pipelines for processing structured and unstructured data.
• They will lead and mentor a team of 4–5 data engineers, ensuring best practices and timely delivery.
• The role requires deep knowledge of Apache Spark, Hadoop ecosystem, Hive, and distributed data processing.
• Experience with SQL, data modeling, and cloud platforms such as AWS, GCP, or Azure is essential.
• Familiarity with Kafka, Airflow, and modern data orchestration tools is an added advantage.
