Hadoop Solutions Developer

Bright Vision Technologies; United States; Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking an experienced Hadoop Solutions Developer to design, build, and operate large-scale data pipelines on Hadoop in a remote setup. You will drive ingestion, transformation, and analytics workloads for enterprise use.

The role requires deep Hadoop ecosystem knowledge, strong software engineering fundamentals, and the ability to deliver reliable, cost-efficient data platforms in production environments across the US.

Qualifications

• Bachelor’s degree in CS, engineering, or related field.
• 5+ years designing and operating Hadoop data pipelines.
• Hands-on Apache Spark in production (Scala, Python, or Java).
• Experience with Hive, HDFS, Sqoop, HBase and Hadoop ecosystem.
• Streaming data platforms such as Kafka, Spark Streaming, or Flink.
• Strong SQL and experience with relational and NoSQL stores.
• Experience with Airflow or Oozie.
• Distributed systems concepts: partitioning, replication, fault tolerance.
• Scripting in Python or Shell.
• Excellent troubleshooting and documentation.

Responsibilities

• Design, develop, and operate end-to-end big-data pipelines on Hadoop.
• Build ETL/ELT workflows with Spark, Hive, Pig, and Sqoop.
• Develop streaming pipelines with Kafka, Spark Streaming, or Flink.
• Tune Spark and MapReduce for performance and cost.
• Design data models and storage on HDFS, Hive, HBase; lakehouse formats.
• Implement data governance, lineage, and quality controls.
• Build monitoring, alerting, and logging for pipelines.
• Collaborate with data scientists to provide curated datasets.
• Automate pipelines with Airflow or Oozie.
• Evaluate new technologies like EMR, Databricks, Snowflake, BigQuery.
• Lead performance reviews and architecture audits.
• Document architectures and runbooks.
• Mentor junior engineers and contribute to standards.

Skills

Hadoop

Apache Spark

Kafka

Airflow

Oozie

Hive

HDFS

Sqoop

Python

Shell

SQL

Kubernetes

Databricks

Delta Lake

Iceberg

Hudi

Education

Bachelor’s degree in CS/Engineering

Tools

Hive

HDFS

Sqoop

HBase

Spark

Job description

Hadoop Solutions Developer -Remote

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.

Job Title

Hadoop Solutions Developer

Location

100% Remote (U.S.)

Position Type

Full-time, Direct W2

Salary Range

$100,000–$150,000 Annually

Experience Required

6+ years

Sponsorship

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.

Job Summary

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.

Key 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.
• Automate pipeline orchestration using Airflow, Oozie, or similar workflow engines, with clean dependency management and clear ownership boundaries.
• Continuously evaluate and adopt new technologies in the big-data and cloud ecosystem (EMR, Databricks, Snowflake, BigQuery) where they offer meaningful improvements.
• 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.
• Mentor junior engineers and contribute to the team’s engineering standards and best practices.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related technical discipline.
• Five or more years of professional experience designing and operating big-data pipelines on Hadoop.
• 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.
• Strong SQL skills and experience working with both relational and NoSQL data stores.
• Experience with workflow orchestration tools such as Airflow or Oozie.
• Solid understanding of distributed systems concepts, including partitioning, replication, and fault tolerance.
• Strong scripting skills in Python or Shell.
• Excellent troubleshooting, debugging, and documentation skills.

Preferred Qualifications

• 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.

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.