Hadoop Big Data Developer

Bright Vision Technologies
Hoboken, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 150K

Job location

Remote
Hoboken, United States of America

Tech stack

Java
Airflow
Apache HTTP Server
Azure
Big Data
Google BigQuery
Cloud Computing
Continuous Integration
Information Engineering
Data Governance
ETL
Serialization
Data Stores
Database Queries
Software Debugging
Distributed Systems
Document-Oriented Databases
Fault Tolerance
Hadoop
Hadoop Distributed File System
MapReduce
HBase
Hive
Python
Machine Learning
NoSQL
Apache Oozie
Cloud Services
Software Engineering
Sqoop
Data Streaming
Unstructured Data
Parquet
Data Logging
Scripting (Bash/Python/Go/Ruby)
Snowflake
Spark
Hdinsight
Electronic Medical Records
Kubernetes
Information Technology
Collibra
Apache Flink
Kafka
Operational Systems
Spark Streaming
Data Management
Api Design
Amazon Web Services (AWS)
Databricks

Job description

We are seeking an experienced Hadoop Big Data 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., Duties: Responsible for consulting on complex initiatives with broad impact and large-scale planning for Software Engineering; reviewing and analyzing complex multi-faceted, larger…
  • 10 days ago

Requirements

  • Bachelor's degree in Computer Science, Engineering, or a 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.

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.

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