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The ideal candidate brings strong experience in Python, SQL, Databricks/PySpark, and modern data engineering practices.\nPrimary Responsibilities \nBuild, scale, and maintain robust data solutions.\nImplement and optimize high-performance data pipelines: extraction, loading, transformation, and orchestration - that are designed for scalability, reliability, maintainability, and speed.\nChampion modern software engineering practices as CI/CD, infrastructure-as-code, containerization, and cloud-native deployments\nCollaborate closely with business stakeholders to transform use cases into production-ready services and solutions, owning the system from concept to production.\nImplement rigorous testing and monitoring practices to maintain superior data quality and integrity.\nRequirements \nEducation & Certificates \nA bachelor's degree or higher in a STEM field, required\nConcentration in Computer Science, Math, Physics or other engineering related field, preferred \nProfessional Experience \n5+ years of experience in data engineering or a related discipline, with a proven track record of success.\nCompetencies & Attributes \nExpertise in Python and SQL, with a strong foundation in data manipulation and analysis.\nProficient with Databricks/PySpark and dbt for data warehousing and data transformation tasks.\nExperience with workflow orchestration tools e.g. Airflow, Dagster\nExperience working with large language models (LLMs) especially prompt engineering, retrieval-augmented generation (RAG)s, and/or vector databases are pluses.\nKnowledge of fundamental principles of machine learning, feature engineering, and knowledge graphs are pluses.\nDemonstrated experience in designing and implementing complex data systems from the ground up.\nProficient in handling large-scale data projects, including data cleaning, ETL, and information retrieval.\nExcellent communication skills required, both verbal and written. \nNimble Gravity is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, state, or local law. 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