{"schemaVersion":"jobsearcher.job.v1","id":"6aefb990a7043371f5c7a369","url":"https://jobsearcher.com/jobs/6aefb990a7043371f5c7a369","canonicalUrl":"https://jobsearcher.com/jobs/6aefb990a7043371f5c7a369","title":"Apache Spark Developer","description":"Apache Spark Developer – Remote\n\nBright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.\n\nThis is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.\n\nJob Title: Apache Spark Developer\nLocation: 100% Remote (U.S.)\nPosition Type: Full-time, Direct W2\nSalary Range: $125,000–$185,000 Annually\nExperience Required: 6+ years\n\nSponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.\n\nJob Summary\nWe 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.\nYou 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.\n\nKey Responsibilities\nDesign, develop, and maintain high-performance distributed data processing applications using Apache Spark.\nBuild scalable batch and real-time ETL/ELT pipelines processing large volumes of enterprise data.\nDevelop Spark applications using PySpark, Scala, or Spark SQL for data transformation, aggregation, and analytics.\nOptimize Spark jobs for memory utilization, partitioning strategies, shuffle performance, and execution efficiency.\nProcess structured, semi-structured, and streaming data from enterprise databases, APIs, Kafka, cloud storage, and data lakes.\nDevelop reusable Spark libraries, data processing frameworks, and metadata-driven ingestion pipelines.\nCollaborate with cloud engineering teams to deploy Spark workloads on Databricks, EMR, Azure Synapse, or Kubernetes.\nImplement data quality validation, reconciliation, monitoring, and automated error handling across distributed pipelines.\nIntegrate Spark applications with enterprise data warehouses, lakehouses, and reporting platforms.\nParticipate in architecture reviews, code reviews, technical design discussions, and Agile development activities.\nTroubleshoot production issues involving distributed processing, cluster performance, resource utilization, and data quality.\nSupport cloud migration initiatives by modernizing legacy ETL workloads into Spark-based architectures.\n\nRequired Skills\nSix or more years of professional software or data engineering experience.\nFour or more years of hands-on Apache Spark development experience in enterprise production environments.\nStrong proficiency in PySpark, Scala, or Spark SQL for distributed data processing.\nDeep understanding of Apache Spark architecture including RDDs, DataFrames, Datasets, Catalyst Optimizer, DAG execution, and Tungsten engine.\nStrong experience with distributed computing concepts including partitioning, shuffling, caching, broadcast joins, and fault tolerance.\nAdvanced SQL skills with databases such as SQL Server, Oracle, PostgreSQL, Snowflake, or Teradata.\nExperience working with Hadoop ecosystem technologies including Hive, HDFS, YARN, and Parquet.\nExperience processing streaming data using Spark Structured Streaming, Apache Kafka, or Event Hubs.\nHands-on experience with cloud platforms including Azure Databricks, AWS EMR, AWS Glue, Azure Synapse Analytics, or Google Dataproc.\nExperience integrating Spark applications with Delta Lake, Apache Iceberg, or Apache Hudi.\nStrong understanding of data warehousing concepts, dimensional modeling, and data lake architecture.\nExperience using Git, CI/CD pipelines, Azure DevOps, GitHub Actions, or Jenkins.\nStrong debugging, troubleshooting, and Spark performance tuning skills.\nExperience working in Agile Scrum development environments.\n\nPreferred Qualifications\nExperience building enterprise Lakehouse architectures using Databricks or Delta Lake.\nFamiliarity with Apache Airflow, Azure Data Factory, AWS Step Functions, or Control-M for workflow orchestration.\nExperience with machine learning workflows using Spark MLlib, MLflow, or feature engineering pipelines.\nKnowledge of Kubernetes, Docker, and containerized Spark deployments.\nExperience implementing Data Quality frameworks using Great Expectations or Deequ.\nFamiliarity with Apache NiFi, Apache Flink, Trino, or Presto.\nExperience working with cloud object storage including Amazon S3, Azure Data Lake Storage (ADLS Gen2), or Google Cloud Storage.\nKnowledge of Infrastructure as Code using Terraform or ARM templates.\nExperience with enterprise monitoring tools including Prometheus, Grafana, Datadog, or OpenTelemetry.\nCloud certifications in Azure, AWS, Databricks, or Apache Spark-related technologies are highly desirable.\n\nProject Environment\nYou will be joining a modern data engineering team responsible for building cloud-native big data platforms supporting enterprise analytics, AI, and business intelligence initiatives. Current projects include:\nEnterprise data lakehouse implementation using Databricks and Delta Lake\nReal-time streaming analytics processing billions of daily events\nLarge-scale customer analytics and behavioral data platforms\nFinancial risk modeling and fraud detection pipelines\nHealthcare clinical and operational analytics solutions\nCloud migration of legacy Hadoop and ETL workloads\nMachine learning feature engineering and model training pipelines\nEnterprise reporting platforms supporting executive dashboards and self-service analytics\nDistributed data processing infrastructure deployed on Azure and AWS\nThis is a hands-on engineering role where you will contribute to distributed system architecture, Spark application development, cloud migration, performance optimization, production support, and continuous improvement of enterprise-scale data processing platforms.\n\nHow to Apply\n\nWould you like to know more about this opportunity? For immediate consideration, please send your resume to Harry@bvteck.com or contact us at (908) 676-4399. Learn more about Bright Vision Technologies at www.bvteck.com.\n\nBright Vision Technologies is an Equal Opportunity Employer.\n\nEqual Employment Opportunity (EEO) Statement\n\nBright 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.\n\nBV 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.\n6uDUiImDxi","company":"Brightvisiontechnologies","rawCompany":"brightvisiontechnologies","city":"Myrtle Point","state":"OR","isRemote":false,"isActive":false,"createdAt":"2026-09-28T11:48:54.839Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Apache Spark Developer","description":"Apache Spark Developer – Remote\n\nBright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.\n\nThis is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.\n\nJob Title: Apache Spark Developer\nLocation: 100% Remote (U.S.)\nPosition Type: Full-time, Direct W2\nSalary Range: $125,000–$185,000 Annually\nExperience Required: 6+ years\n\nSponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.\n\nJob Summary\nWe 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.\nYou 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.\n\nKey Responsibilities\nDesign, develop, and maintain high-performance distributed data processing applications using Apache Spark.\nBuild scalable batch and real-time ETL/ELT pipelines processing large volumes of enterprise data.\nDevelop Spark applications using PySpark, Scala, or Spark SQL for data transformation, aggregation, and analytics.\nOptimize Spark jobs for memory utilization, partitioning strategies, shuffle performance, and execution efficiency.\nProcess structured, semi-structured, and streaming data from enterprise databases, APIs, Kafka, cloud storage, and data lakes.\nDevelop reusable Spark libraries, data processing frameworks, and metadata-driven ingestion pipelines.\nCollaborate with cloud engineering teams to deploy Spark workloads on Databricks, EMR, Azure Synapse, or Kubernetes.\nImplement data quality validation, reconciliation, monitoring, and automated error handling across distributed pipelines.\nIntegrate Spark applications with enterprise data warehouses, lakehouses, and reporting platforms.\nParticipate in architecture reviews, code reviews, technical design discussions, and Agile development activities.\nTroubleshoot production issues involving distributed processing, cluster performance, resource utilization, and data quality.\nSupport cloud migration initiatives by modernizing legacy ETL workloads into Spark-based architectures.\n\nRequired Skills\nSix or more years of professional software or data engineering experience.\nFour or more years of hands-on Apache Spark development experience in enterprise production environments.\nStrong proficiency in PySpark, Scala, or Spark SQL for distributed data processing.\nDeep understanding of Apache Spark architecture including RDDs, DataFrames, Datasets, Catalyst Optimizer, DAG execution, and Tungsten engine.\nStrong experience with distributed computing concepts including partitioning, shuffling, caching, broadcast joins, and fault tolerance.\nAdvanced SQL skills with databases such as SQL Server, Oracle, PostgreSQL, Snowflake, or Teradata.\nExperience working with Hadoop ecosystem technologies including Hive, HDFS, YARN, and Parquet.\nExperience processing streaming data using Spark Structured Streaming, Apache Kafka, or Event Hubs.\nHands-on experience with cloud platforms including Azure Databricks, AWS EMR, AWS Glue, Azure Synapse Analytics, or Google Dataproc.\nExperience integrating Spark applications with Delta Lake, Apache Iceberg, or Apache Hudi.\nStrong understanding of data warehousing concepts, dimensional modeling, and data lake architecture.\nExperience using Git, CI/CD pipelines, Azure DevOps, GitHub Actions, or Jenkins.\nStrong debugging, troubleshooting, and Spark performance tuning skills.\nExperience working in Agile Scrum development environments.\n\nPreferred Qualifications\nExperience building enterprise Lakehouse architectures using Databricks or Delta Lake.\nFamiliarity with Apache Airflow, Azure Data Factory, AWS Step Functions, or Control-M for workflow orchestration.\nExperience with machine learning workflows using Spark MLlib, MLflow, or feature engineering pipelines.\nKnowledge of Kubernetes, Docker, and containerized Spark deployments.\nExperience implementing Data Quality frameworks using Great Expectations or Deequ.\nFamiliarity with Apache NiFi, Apache Flink, Trino, or Presto.\nExperience working with cloud object storage including Amazon S3, Azure Data Lake Storage (ADLS Gen2), or Google Cloud Storage.\nKnowledge of Infrastructure as Code using Terraform or ARM templates.\nExperience with enterprise monitoring tools including Prometheus, Grafana, Datadog, or OpenTelemetry.\nCloud certifications in Azure, AWS, Databricks, or Apache Spark-related technologies are highly desirable.\n\nProject Environment\nYou will be joining a modern data engineering team responsible for building cloud-native big data platforms supporting enterprise analytics, AI, and business intelligence initiatives. Current projects include:\nEnterprise data lakehouse implementation using Databricks and Delta Lake\nReal-time streaming analytics processing billions of daily events\nLarge-scale customer analytics and behavioral data platforms\nFinancial risk modeling and fraud detection pipelines\nHealthcare clinical and operational analytics solutions\nCloud migration of legacy Hadoop and ETL workloads\nMachine learning feature engineering and model training pipelines\nEnterprise reporting platforms supporting executive dashboards and self-service analytics\nDistributed data processing infrastructure deployed on Azure and AWS\nThis is a hands-on engineering role where you will contribute to distributed system architecture, Spark application development, cloud migration, performance optimization, production support, and continuous improvement of enterprise-scale data processing platforms.\n\nHow to Apply\n\nWould you like to know more about this opportunity? For immediate consideration, please send your resume to Harry@bvteck.com or contact us at (908) 676-4399. Learn more about Bright Vision Technologies at www.bvteck.com.\n\nBright Vision Technologies is an Equal Opportunity Employer.\n\nEqual Employment Opportunity (EEO) Statement\n\nBright 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.\n\nBV 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.\n6uDUiImDxi","datePosted":"2026-09-28T11:48:54.839Z","dateModified":"2026-09-28T11:48:54.839Z","hiringOrganization":{"@type":"Organization","name":"Brightvisiontechnologies","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Myrtle Point","addressRegion":"OR","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"6aefb990a7043371f5c7a369"},"url":"https://jobsearcher.com/jobs/6aefb990a7043371f5c7a369"}}