Senior Data Engineer

Job Requirement:

• A robust background in software engineering with significant experience in data engineering.
• Expert-level proficiency in Python, PySpark, and SQL, with the ability to architect and optimize complex data workflows.
• Understanding of Apache Spark architecture, including its execution model and memory management, with the ability to analyze Spark job metrics (task execution times, shuffle operations, and executor memory usage) to optimize ETL pipelines
• Proven experience in designing real-time streaming data pipelines for high-throughput, low-latency systems.
• Proven experience in handling and working with true Big Data (daily volume in TBs)
• Hands-on experience with Azure and AWS cloud services
• Hands-on experience with Databricks, Snowflake, and Airflow (admin experience in any of these platforms is a plus.

Nice to have :

• Practical experience in MLOps, including taking machine learning POCs through the full lifecycle to production deployment.
• Experience with MLflow for managing machine learning life cycles.
• Experience working with vector embeddings, RAG, and vector search, with a strong understanding of various embedding models.
• Experience working on search-focused projects - implementing search logic and optimization techniques
• Strong knowledge of mathematics and statistics for solving complex ranking and scoring problems.
• Previous work on building and deploying AI applications.
• Experience deploying Large Language Models (LLMs) in production environments.

Education:

• Bachelor's or Master’s degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.

GlobalLogic estimates the starting pay range for this role to be performed in Denver, CO, to be $110,000 to $125,000, and reflects base salary only. This pay range is provided as a good-faith estimate, and the amount offered may be higher or lower. GlobalLogic takes many factors into consideration in making an offer, including candidate qualifications, work experience, operational needs, travel and onsite requirements, internal peer equity, prevailing wage, responsibilities, and other market and business considerations.