Job Summary The Data Engineer will design, develop, optimize, and maintain scalable data platforms and pipelines supporting enterprise analytics and business intelligence initiatives. The role requires strong expertise in modern data engineering technologies, cloud-based data platforms, ETL/ELT orchestration, distributed data processing, and lakehouse architectures. The engineer will work closely with business and technical stakeholders in an onsite environment to deliver reliable, secure, and scalable data solutions. The position requires 5+ years of experience in Data Engineering, ETL Development, or Data Platform Engineering. Key Responsibilities

• Design, develop, and optimize scalable data pipelines for batch and real-time data processing.
• Build and maintain robust ETL/ELT solutions using Python, SQL, and SSIS.
• Develop and manage workflow orchestration using Apache Airflow.
• Implement data transformation and processing solutions using Apache Spark.
• Design, optimize, and support data lakehouse architectures using Databricks and Apache Iceberg.
• Ensure data quality, integrity, security, and governance across data platforms.
• Monitor, troubleshoot, and optimize data ingestion and processing workflows.
• Collaborate with business analysts, data scientists, architects, and application teams to understand data requirements and deliver scalable solutions.
• Perform performance tuning of databases, Spark jobs, and data pipelines.
• Support production deployments and provide ongoing maintenance for critical data systems.
• Follow best practices for coding, documentation, testing, and release management. Required Qualifications
• 5+ years of experience in Data Engineering, ETL Development, or Data Platform Engineering.
• Strong experience with SQL, including complex query development, data modeling, and performance tuning.
• Proficiency in Python for data engineering and ETL development.
• Hands-on experience with SSIS (SQL Server Integration Services).
• Experience designing and managing workflows using Apache Airflow.
• Strong knowledge of Apache Spark for large-scale data processing.
• Experience working with Apache Iceberg tables and lakehouse architectures.
• Hands-on experience with Databricks for data engineering and analytics workloads.
• Strong understanding of data warehousing, ETL/ELT concepts, and distributed data systems.
• Experience with data quality, monitoring, and troubleshooting techniques.
• Proven experience delivering enterprise-scale data solutions using modern data technologies.
• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. Preferred Qualifications
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Familiarity with CI/CD pipelines and DevOps practices for data platforms.
• Knowledge of data governance, metadata management, and security best practices.
• Experience supporting large-scale enterprise data environments.

Notes:

Mandatory Areas Must Have Skills

• Data Engineer Skill 1
• 8 + Years of exp in Data Engineering Skill 2
• 5 + Years of Exp in Python, ETL/ELT, SSIS Skill 3
• 4+ Years of exp in AWS/ Azure /GCP Good To have Skills
• Skill 1
• Yrs of Exp
• N/A Skill 2
• Yrs of Exp
• N/A Skill 3
• Yrs of Exp
• N/A Skill 4
• Yrs of Exp
• N/A Mandatory if Applicable Domain Experience (If any )
• N/A Must have Certifications
• N/A Location
• Norfolk, VA Onsite Requirement
• Y/N•Y Number of days onsite•3 Days If Onsite•Office Address•