Data Engineer

Job Title: Data Engineer (Scala + AWS + Spark) Locations: McLean, VA / Richmond, VA / Chicago, IL Experience: 7+ Years Visa: H1B Interview Process: In-Person / Face-to-Face (F2F) Job Description We are seeking a highly skilled Data Engineer with strong expertise in Scala, AWS, and Apache Spark. The ideal candidate will have 7+ years of hands-on experience building scalable data pipelines, distributed processing systems, and cloud-native data solutions. Key Responsibilities • Design, build, and optimize large-scale data pipelines using Scala and Spark. • Develop and maintain ETL/ELT workflows across AWS services. • Work on distributed data processing using Spark, Hadoop, or similar. • Build data ingestion, transformation, cleansing, and validation routines. • Optimize pipeline performance and ensure reliability in production environments. • Collaborate with cross-functional teams to understand requirements and deliver robust solutions. • Implement CI/CD best practices, testing, and version control. • Troubleshoot and resolve issues in complex data flow systems. Required Skills & Experience • 7+ years of Data Engineering experience. • Strong programming experience with Scala (must-have). • Hands-on experience with Apache Spark (core, SQL, streaming). • Solid experience with AWS cloud services (Glue, EMR, Lambda, S3, EC2, IAM, etc.). • High proficiency in SQL and relational/noSQL data stores. • Strong understanding of data modeling, data architecture, and distributed systems. • Experience with workflow orchestration tools (Airflow, Step Functions, etc.). • Strong communication and problem-solving skills. Preferred Skills • Experience with Kafka, Kinesis, or other streaming platforms. • Knowledge of containerization tools like Docker or Kubernetes. • Background in data warehousing or modern data lake architectures.