Big Data Engineer

Benefits:

ONSITE

Competitive salary Opportunity for advancement Big Data Engineer Location: Chicago, IL (Day 1 Onsite) Job Type: Contract / Full Time Experience: 8+ yrs Duration: Long Term We are seeking an experienced Big Data Engineer to design, develop, and optimize enterprise-scale big data solutions. The ideal candidate will have strong hands-on expertise in the Hadoop ecosystem, Spark, Scala, Hive, Apache NiFi, and Kafka, along with experience building scalable data pipelines and supporting modern CI/CD practices. Candidates should have worked directly with clients, participated in requirement gathering sessions, and delivered end-to-end Big Data implementations. Key Responsibilities

• Design, develop, and optimize large-scale data processing pipelines using Spark, Scala, and Hive.
• Build and maintain data ingestion workflows using Apache NiFi.
• Develop and support real-time data streaming solutions using Apache Kafka.
• Monitor application logs and system health using Kibana, Elasticsearch, and Logstash.
• Implement and support CI/CD pipelines using Git, Jenkins, and Nexus.
• Ensure data quality, integrity, and governance across Big Data platforms.
• Participate in architecture discussions and recommend scalable design solutions.
• Troubleshoot and resolve complex production issues across the Big Data stack.
• Collaborate with cross-functional teams in an Agile environment.
• Mentor junior engineers and contribute to technical best practices.

Required Qualifications

• 8+ years of experience in Big Data technologies.
• Strong hands-on experience with Spark, Scala, Hive (HQL), and the Hadoop ecosystem.
• Experience implementing Apache NiFi and Apache Kafka.
• Proficiency in Shell Scripting or Python.
• Experience with PostgreSQL.
• Familiarity with scheduling tools such as Oozie and Control-M.
• Working knowledge of Git, Jenkins, Nexus, Maven, Ansible, and SonarQube.
• Strong understanding of CI/CD practices.
• Experience in client-facing roles, including requirement gathering workshops.
• Minimum of two end-to-end Big Data implementation projects.
• Ability to work independently and contribute effectively within Agile teams.