Technology and Operations - Data Engineer

Job Title: Technology and Operations - Data Engineer Location: Sterling - 45580 Terminal Drive\_US28-Virginia We are looking for a seasoned Data Engineer with a strong foundation in big data technologies and a growing proficiency in AI/ML systems. This individual will bring deep expertise in large-scale data processing frameworks (both open-source and proprietary), OLAP/OLTP systems, and real-time data streaming. The ideal candidate will also demonstrate a passion for enabling AI-driven solutions through robust, scalable data infrastructure. Key Responsibilities: • Design, develop, and maintain highly scalable, fault-tolerant real-time, near real-time, and batch data pipelines. • Implement data quality checks, validation, and cleaning processes to ensure high data accuracy and integrity. • Continuously monitor and optimize data pipelines and databases for performance, resource utilization, and cost efficiency. • Uphold high standards in code quality, testing, and documentation. • Mentor junior data engineers and provide technical leadership within the team. • Perform exploratory and quantitative analytics, data mining, and discovery to support AI/ML initiatives. • Collaborate with data analysts and business stakeholders to make data accessible and actionable. • Participate in 24x7 platform support rotations as needed. Required Qualifications: • Bachelor’s degree or higher in Computer Science or a related field. • 7+ years of experience in data engineering roles. • Proficiency in programming languages such as Scala, Python, or Java. • Expertise in distributed data processing frameworks like Apache Spark or Flink. • Experience with stream processing systems such as Kafka or Kinesis. • Strong knowledge of cloud platforms (e.g., AWS) and cloud-native data platforms like Databricks, Snowflake, or Redshift. • Solid understanding of SQL, schema design, dimensional modeling, and ETL best practices. • Experience with workflow orchestration tools such as Apache Airflow. • Familiarity with CI/CD pipelines, preferably GitHub Actions. • Strong technical documentation and issue-tracking skills. • Experience with analytics tools such as Looker or Tableau. • Demonstrated ability to adopt and integrate new technologies. • Experience in direct-to-consumer digital businesses is a plus. Preferred Qualifications: • Familiarity with statistical modeling libraries (e.g., Scikit-learn, XGBoost, TensorFlow). • Experience with AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. • Exposure to GenAI technologies, including LLMs and RAG pipelines.