Big Data Engineer (No C2C)

Experis

Virginia

On-site

USD 99,000 - 103,000

Full time

2 days ago

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Benefits offered by this job

Medical and Prescription Drug Plans

Dental Plan

Vision Plan

Health Savings Account

Health Flexible Spending Account

Dependent Care Flexible Spending Area

401(k), Plus Match

Weekly Pay

Job summary

Experis is hiring a Big Data Engineer to join the Data Engineering team in McLean, VA, onsite. The role focuses on building scalable data pipelines using Hadoop, Spark, Python, and Scala to support analytics initiatives.

You will design, develop, test, and optimize end-to-end data flows, ensure data quality, and collaborate with data scientists and analysts to enable data-driven decisions. Candidates should have 5+ years of experience and a solid software engineering background.

Qualifications

Bachelor’s degree in CS/IS or related field with at least 5 years of relevant experience.
Strong experience with enterprise-grade data pipelines and Big Data technologies.
Proficient in SQL, window functions, joins, and handling NULLs and duplicates.
Experience with test automation, build automation, and configuration management.
Experience collaborating with data scientists and analysts.

Responsibilities

Design, develop, and maintain large-scale data processing pipelines using Hadoop, Spark, Python, and Scala.
Build scalable, efficient data ingestion, storage, transformation, and analysis solutions.
Optimize pipelines for performance, scalability, and reliability; troubleshoot production issues.
Develop automated testing frameworks and implement continuous testing for data quality.
Collaborate with data scientists and analysts to enable data-driven decisions.

Skills

5+ years experience

Big Data

data pipeline

SQL

Agile

test automation

Education

Bachelor’s degree in CS/IS or related

Tools

Hadoop

Spark

Hive

Trino

Python

Scala

Job description

Experis is hiring a Big Data Engineer to join the Data Engineering team, supporting analytics and data platform initiatives. The position focuses on creating dependable, scalable data pipelines and improving end-to-end data processing for analytics use cases.

Role Responsibilities

Design, develop, and maintain large-scale data processing pipelines using Big Data technologies including Hadoop, Spark, Python, and Scala.
Build scalable, efficient, and reliable solutions for data ingestion, storage, transformation, and analysis.
Optimize and enhance existing data pipelines to improve performance, scalability, and reliability, including troubleshooting production issues.
Develop automated testing frameworks and implement continuous testing to support data quality assurance.
Work with cross-functional partners, including data scientists and analysts, to enable data-driven decision-making.

Required Qualifications

Bachelor’s degree in Computer Science, Information Systems, or a related discipline, plus at least 5 years of related experience, or equivalent training and/or work experience.
Proven technical expertise in object-oriented and database technologies and concepts, with experience delivering enterprise-quality solutions.
Strong software engineering background, including experience with test automation, build automation, and configuration management, along with iterative or Agile delivery experience.
Hands-on experience with Big Data technologies such as Hadoop, Spark, Hive, and Trino, including debugging and mitigation for issues such as data skew and resource-related job failures.
Strong SQL skills, including window functions, joins, and complex queries, with the ability to write and optimize SQL while handling edge cases including NULLs, duplicates, and ordering.