Databricks Developer (Java & Apache Spark) with IRS MBI Clearance required
Job Description
Job Description
This is a remote position.
Job Title: Databricks Developer (Java & Apache Spark)
Location: Remote
Duration: Full-Time
NEED IRS MBI Clearance.
We are looking for a Databricks Developer who can design, build, and support large-scale data processing solutions. This role focuses on working with complex, high-volume data in a secure environment. You should be comfortable writing clean Java code, building Spark jobs, and improving performance in distributed systems.
You’ll work closely with engineers, analysts, and business teams to deliver reliable data pipelines that scale well and meet security and compliance requirements.
What You’ll Do
Build and maintain data pipelines using Apache Spark on Databricks
Write clean and efficient Java (Java 8 or higher) following best coding practices
Work with large structured and semi-structured data sets
Tune Spark jobs to improve performance, stability, and cost
Partner with other teams to understand requirements and deliver solutions
Make sure data handling follows security and governance standards
Investigate and fix issues in production environments
What We’re Looking For
Active federal background clearance (client-issued laptop is a plus)
Bachelor’s degree in Computer Science or a related field
8+ years of hands-on experience in data engineering or big data development
Technical Skills
Data & Systems
Experience working with large enterprise or government data systems
Good understanding of data structures, security, and compliance
Java
Strong experience with Java 8 or newer
Comfortable with Streams, Lambdas, and object-oriented design
Apache Spark
Hands-on experience with Spark Core, Spark SQL, and DataFrames
Understanding of RDDs and when to use them
Experience with batch processing and streaming
Strong skills in Spark performance tuning
Able to debug jobs using Spark UI and logs
Big Data Tools
Experience with tools like HDFS, Hive, or HBase
Familiar with Kafka, S3, or cloud-based data lakes
Experience with Parquet, Avro, or ORC formats
ETL & Data Processing
Experience building batch and real-time ETL pipelines
Skilled in data cleansing, transformation, and enrichment
DevOps & Deployment
Experience running Spark on YARN, Kubernetes, or cloud platforms
Familiar with CI/CD tools like Jenkins or GitHub Actions
Experience with monitoring tools and production logs
Testing & Code Quality
Unit testing using JUnit or TestNG
Experience with Mockito or similar tools
Comfortable validating data and testing Spark jobs
Ways You’ll Succeed
You’re used to working in Agile teams
You document your work clearly
You stay calm and focused when troubleshooting production issues
Nice to Have:
Experience with Scala or Python in Spark
Hands-on experience with Databricks or Google Dataproc
Knowledge of Delta Lake or Apache Iceberg
Background in data modeling and performance design