Spark Developer

Matlen Silver; Jersey City (NJ); On-site; USD 140,000 - 190,000; Full time

Job summary

Matlen Silver is seeking a Senior Apache Spark Developer to design and build a modern data processing platform. The role focuses on distributed data processing with Spark, leveraging Kafka and an enterprise Databricks/AWS ecosystem for real-time and batch workloads.

The ideal candidate will contribute to cloud adoption, scalable data pipelines, and migration initiatives while delivering robust, observable, and efficient Spark solutions. Collaboration with cross-functional teams is essential.

Qualifications

• 5+ years of hands-on development experience with Apache Spark.
• Strong expertise in Spark SQL, Structured Streaming, DataFrames/Datasets.
• Experience tuning performance and optimizing Spark workloads.
• Experience integrating Spark with Apache Kafka.
• Proficiency in Java and Python.
• Experience designing and supporting large-scale distributed systems.

Responsibilities

• Design, develop, and optimize Spark-based applications for large-scale data processing.
• Build streaming and batch data solutions leveraging Apache Kafka and Apache Spark.
• Develop reusable frameworks and components supporting enterprise data engineering initiatives.
• Support migration to Databricks and AWS.
• Collaborate with architects and platform engineers to implement cloud-native data solutions.
• Optimize Spark jobs for performance, scalability, reliability, and operational efficiency.
• Participate in system design, code reviews, testing, and production support.
• Implement CI/CD, monitoring, and observability practices for distributed data applications.
• Troubleshoot issues across Spark, Kafka, Databricks, and cloud environments.

Skills

Apache Spark

Spark SQL

Structured Streaming

DataFrames/Datasets

Performance tuning

Kafka integration

Java

Python

Distributed systems

Tools

Databricks

AWS

Kafka

Job description

We are seeking a Senior Apache Spark Developer to help build and expand our next-generation data processing platform. This role will focus on designing and developing distributed data processing solutions using Apache Spark while leveraging an existing enterprise Kafka ecosystem.

The successful candidate will play a critical role in scaling our data processing capabilities, enabling cloud adoption, and supporting strategic migration initiatives involving Databricks and AWS. This position offers the opportunity to work on high-volume, mission-critical data platforms processing large-scale real-time and batch workloads.

Key Responsibilities

• Design, develop, and optimize Spark-based applications for large-scale data processing.
• Build streaming and batch data solutions leveraging Apache Kafka and Apache Spark.
• Develop reusable frameworks and components supporting enterprise data engineering initiatives.
• Support migration efforts from on-premises data platforms to Databricks and AWS.
• Collaborate with architects and platform engineers to implement cloud-native data solutions.
• Optimize Spark jobs for performance, scalability, reliability, and operational efficiency.
• Participate in system design, code reviews, testing, and production support activities.
• Implement CI/CD, monitoring, and observability practices for distributed data applications.
• Troubleshoot and resolve complex issues across Spark, Kafka, Databricks, and cloud environments and with other enterprise messaging systems.

Required Qualifications

• 5+ years of hands-on development experience with Apache Spark.
• Strong expertise in:
• Spark SQL
• Structured Streaming
• DataFrames/Datasets
• Performance tuning and optimization
• Experience integrating Spark with Apache Kafka.
• Java
• Python
• Experience designing and supporting large-scale distributed systems.
• Solid understanding of software engineering principles, object-oriented design, and testing practices.
• Experience working with relational and distributed data platforms.

Preferred Qualifications

• AWS experience, including services such as:
• S3
• EMR
• Glue
• Lambda
• ECS/EKS
• Experience supporting large-scale cloud migration initiatives.
• Experience with lakehouse architectures and modern data platform patterns.
• Experience handling multi-terabyte or petabyte-scale datasets.
• Financial services or regulated industry experience.

Ideal Candidate Profile (for both roles) will stand out if you have:

• Delivered large-scale cloud migration programs involving hundreds of terabytes or petabytes of data.
• Built or modernized enterprise data platforms using Spark, Kafka, Databricks, and AWS.
• Strong software engineering fundamentals and expertise in Java and/or Python.
• Experience designing highly scalable, resilient, and cost-efficient distributed systems.
• Proven ability to influence architecture decisions and work across multiple engineering teams.
• Ability to come up with iterative O(n) runtime O(1) space solutions to Easy DP problems