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About the Role

We are seeking an experienced Apache Spark Developer to design, develop, and optimize large-scale distributed data processing applications supporting enterprise analytics, machine learning, real-time reporting, and cloud-based data platforms. This role focuses on building high-performance Spark applications capable of processing billions of records across structured and semi-structured data sources while delivering scalable, reliable, and cost-efficient data pipelines. You will work closely with data architects, data engineers, cloud platform teams, machine learning engineers, and business intelligence developers to build modern data processing solutions leveraging Apache Spark, cloud-native technologies, and distributed computing frameworks. The ideal candidate possesses deep expertise in Spark architecture, distributed systems, performance optimization, and cloud-based big data ecosystems.

Responsibilities

Design, develop, and maintain high-performance distributed data processing applications using Apache Spark.
Build scalable batch and real-time ETL/ELT pipelines processing large volumes of enterprise data.
Develop Spark applications using PySpark, Scala, or Spark SQL for data transformation, aggregation, and analytics.
Optimize Spark jobs for memory utilization, partitioning strategies, shuffle performance, and execution efficiency.
Process structured, semi-structured, and streaming data from enterprise databases, APIs, Kafka, cloud storage, and data lakes.
Develop reusable Spark libraries, data processing frameworks, and metadata-driven ingestion pipelines.
Collaborate with cloud engineering teams to deploy Spark workloads on Databricks, EMR, Azure Synapse, or Kubernetes.
Implement data quality validation, reconciliation, monitoring, and automated error handling across distributed pipelines.
Integrate Spark applications with enterprise data warehouses, lakehouses, and reporting platforms.
Participate in architecture reviews, code reviews, technical design discussions, and Agile development activities.
Troubleshoot production issues involving distributed processing, cluster performance, resource utilization, and data quality.
Support cloud migration initiatives by modernizing legacy ETL workloads into Spark-based architectures.

Requirements

Six or more years of professional software or data engineering experience.
Four or more years of hands-on Apache Spark development experience in enterprise production environments.
Strong proficiency in PySpark, Scala, or Spark SQL for distributed data processing.
Deep understanding of Apache Spark architecture including RDDs, DataFrames, Datasets, Catalyst Optimizer, DAG execution, and Tungsten engine.
Strong experience with distributed computing concepts including partitioning, shuffling, caching, broadcast joins, and fault tolerance.
Advanced SQL skills with databases such as SQL Server, Oracle, PostgreSQL, Snowflake, or Teradata.
Experience working with Hadoop ecosystem technologies including Hive, HDFS, YARN, and Parquet.
Experience processing streaming data using Spark Structured Streaming, Apache Kafka, or Event Hubs.
Hands-on experience with cloud platforms including Azure Databricks, AWS EMR, AWS Glue, Azure Synapse Analytics, or Google Dataproc.
Experience integrating Spark applications with Delta Lake, Apache Iceberg, or Apache Hudi.
Strong understanding of data warehousing concepts, dimensional modeling, and data lake architecture.
Experience using Git, CI/CD pipelines, Azure DevOps, GitHub Actions, or Jenkins.
Strong debugging, troubleshooting, and Spark performance tuning skills.
Experience working in Agile Scrum development environments.

Skills

Apache Spark
PySpark
Scala
Spark SQL
Distributed Computing
SQL
Hadoop Ecosystem
Hive
HDFS
YARN
Parquet
Spark Structured Streaming
Apache Kafka
Event Hubs
Azure Databricks
AWS EMR
AWS Glue
Azure Synapse Analytics
Google Dataproc
Delta Lake
Apache Iceberg
Apache Hudi
Data Warehousing
Dimensional Modeling
Data Lake Architecture
Git
CI/CD
Azure DevOps
GitHub Actions
Jenkins
Agile Scrum

Location

100% Remote (U.S.)

Work Type

Full-time
Direct W2

Experience Level

6+ years

Salary/Compensations

$125,000–$185,000 Annually

About the Company

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Equal Opportunity

Bright Vision Technologies is an Equal Opportunity Employer.
Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.
BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.