Bright Vision Technologies

Bright Vision Technologies

Hadoop Solutions Developer

Sacate, Arizona · Senior · Full-time

No sponsorship$100k-$150kDetected 14 days ago
PythonJavaScalaDistributed SystemsSQLNoSQLBigQuerySnowflakeDatabricksAWSAzureCloud PlatformsKubernetesCI/CDKafkaMachine LearningSparkAirflowData EngineeringAI OrchestrationPerformance ManagementEHR/EMRCollaborationHadoop

Stay score

odds of building a lasting career here

59Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level III)83
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~45% per draw at Level III). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

Personalize to your clock →

H-1B wage level

the lottery is wage-weighted — each level is one more entry

Level I · 1×
Level I$92,1231 entry
Level II$113,7142 entries
Level III$135,3043 entries
Level IV$156,8944 entries

$13,714 more$113,714 — moves this role to Level II and 2 lottery entries. That figure is inside the range the employer already advertised.

Based on the DOL prevailing wage for this occupation and worksite, a base salary of $113,714 would place this position at wage Level II. That figure is within the posted range, and I'd like to target it. This role classifies under "Software Developers" for prevailing-wage purposes.

DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · Phoenix-Mesa-Chandler, AZ. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.

Employer immigration record

from this employer's Department of Labor filings

Files H-1B transfers

13 transfer filings in the last year, covering 13 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

Community outcomes

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About the role

  • We are seeking an experienced Hadoop Developer to design, build, and operate large-scale data processing pipelines and analytics platforms on Hadoop and related big-data ecosystems.
  • In this role you will be responsible for ingesting, transforming, and analyzing massive volumes of structured and unstructured data to support enterprise analytics, machine learning, and reporting workloads.
  • The ideal candidate will combine deep technical expertise across the Hadoop ecosystem with strong software engineering fundamentals and a clear understanding of how to deliver reliable, performant, and cost-effective data platforms in production environments.

Responsibilities

  • Design, develop, and operate end-to-end big-data pipelines on Hadoop, ingesting data from a diverse mix of relational, file-based, streaming, and API-driven sources.
  • Build robust ETL/ELT workflows using Apache Spark, Hive, Pig, and Sqoop, with strong attention to data quality, idempotency, error handling, and recoverability.
  • Develop high-throughput streaming data pipelines using Kafka, Spark Streaming, or Flink, and integrate them with downstream analytical and operational systems.
  • Optimize Spark and MapReduce jobs through careful tuning of partitioning, memory, serialization, and skew handling to meet demanding SLAs at minimal cost.
  • Design and maintain data models and storage layouts on HDFS, Hive, HBase, and modern lakehouse formats (Parquet, ORC, Delta, Iceberg, Hudi) to balance flexibility and performance.
  • Implement data governance, lineage, and quality controls in collaboration with data governance and security teams.
  • Build robust monitoring, alerting, and logging strategies for big-data pipelines, including job-level SLAs and proactive failure detection.
  • Partner with data scientists and analysts to deliver curated, reliable, and well-documented datasets that accelerate their work.
  • Lead performance reviews and architecture audits of existing pipelines, proposing concrete refactoring and optimization initiatives.
  • Document data architectures, schemas, pipeline behaviors, and operational runbooks in a way that makes the platform supportable as the team scales.

Requirements

  • Bachelor's degree in Computer Science, Engineering, or a related technical discipline.
  • Strong hands-on expertise with Apache Spark (Scala, Python, or Java) in production environments.
  • Solid experience with Hive, HDFS, Sqoop, HBase, and the broader Hadoop ecosystem.
  • Hands-on experience with streaming data platforms such as Kafka, Spark Streaming, or Flink.
  • Experience with workflow orchestration tools such as Airflow or Oozie.
  • Experience Required: 6+ years

Nice to have

  • Experience operating Hadoop on cloud platforms such as AWS EMR, Azure HDInsight, or Databricks.
  • Familiarity with modern lakehouse formats (Delta, Iceberg, Hudi).
  • Exposure to data governance tooling such as Apache Atlas or Collibra.
  • Experience with Kubernetes-based data platforms (Spark-on-K8s, Trino).
  • Hands-on experience with CI/CD and infrastructure-as-code in data engineering workflows.

Skills

  • Hadoop Solutions Developer - Remote
  • This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
  • Hadoop Solutions Developer
  • 100% Remote (U.S.)

Compensation

  • $100,000-$150,000 Annually

Benefits

  • Learn more about Bright Vision Technologies at www.bvteck.com.
  • Bright Vision Technologies is an

Company info

  • We are unable to sponsor new H-1B visa petitions for this position.

Equal opportunity

  • Equal Opportunity Employer.
  • Equal Employment Opportunity (EEO) Statement

Visa & Work Authorization

  • We are unable to sponsor new H-1B visa petitions for this position.

This listing is sourced directly from Bright Vision Technologies's careers page and normalized into a canonical job model.