Bigdata engineer

Role Overview

We are seeking an experienced Big Data Engineer to design, build, and optimize large-scale data processing systems. This role partners closely with engineering, data, and analytics teams to deliver scalable, reliable data pipelines that support data-driven decision-making. The ideal candidate has strong experience with distributed systems, cloud platforms, and modern big data technologies.

Responsibilities:

• Design, develop, and maintain scalable data pipelines using technologies such as Spark, Hadoop, Python, and Scala.

• Build and optimize data ingestion, transformation, and storage solutions for large-scale datasets.

• Optimize existing data pipelines for performance, scalability, and reliability.

• Collaborate with cross-functional teams to translate business requirements into technical solutions.

• Monitor, troubleshoot, and resolve data pipeline issues in production environments.

• Implement automated testing and data quality checks across pipelines.

• Stay current with emerging big data and cloud technologies to continuously improve the platform.

• Support data scientists and analysts by enabling reliable access to high-quality data.

Qualifications:

• Bachelor's degree in Computer Science or a related field, or equivalent experience.

• 5 years of experience building enterprise-scale data solutions.

• Strong experience with big data technologies such as Spark, Hadoop, Hive, and Trino.

• Proficiency in Python or Scala, with solid object-oriented and/or functional programming skills.

• Strong SQL skills, including complex queries, joins, and window functions.

• Experience working with large datasets and troubleshooting performance, scalability, and data quality issues.

• Experience with cloud platforms, preferably AWS (e.g., S3, EMR, Glue, Athena, Lambda).

• Familiarity with Agile development practices and CI/CD pipelines.

• Strong communication skills and ability to work effectively in a fast-paced environment.

Preferred Qualifications:

• Experience managing production ETL or data pipeline systems.

• Exposure to AI-assisted development tools (e.g., Copilot, ChatGPT, Q Developer).

• Experience with Spark performance tuning and optimization.

• AWS certifications or equivalent cloud experience.

Note:

Must be local to DC/MD/VA, is required to take an assessment, and needs to attend an F2F interview