Principle/Senior Data Engineer Houston Hybrid - 4 days in the office per week Up to $140k bonus Right to work in the US This privately held enterprise operates a diverse portfolio spanning automotive, hospitality, entertainment, conservation, and adventure industries. It is driven by a commitment to innovation, sustainability, and creating lasting value through ethical practices and global impact. The Role As a Principal Data Engineer, you'll architect, implement, and manage robust, scalable data platforms to support advanced analytics, machine learning, and real-time data processing. You'll collaborate with cross-functional teams to design modern data solutions while mentoring junior team members. Key Responsibilities: Design scalable data solutions using Databricks Delta Lake, Data Warehousing, and Lakehouse architectures. Build and optimize data pipelines for large-scale data ingestion, processing, and storage. Leverage cloud technologies (AWS or Azure) such as EC2, RDS, S3, Glue, and Lambda to enhance data handling. Develop and maintain high-performance data models, SQL queries, and ETL/ELT workflows. Implement CI/CD pipelines and version control practices (Git). Collaborate with data scientists, analysts, and machine learning engineers to support analytical models. Ensure compliance with data governance, security, and best practices for cloud data infrastructure. Monitor and troubleshoot pipeline performance to minimize costs and improve scalability. Lead data engineering projects, mentor junior engineers, and stay updated on emerging technologies. Your Skills and Experience Please apply if you have: Strong experience with Databricks (Delta Lake, Unity Catalog, Lakehouse). Expertise in AWS or Azure cloud services. Proficiency in Python, PySpark, and SQL for data processing. Hands-on experience with big data technologies like Apache Spark and Kafka. RDBMS and data warehousing (data modeling, analysis, and stored procedures). Familiarity with CI/CD pipelines and version control (Git). Experience with agile methodologies. 5-8 years of hands-on experience in data engineering and large-scale pipeline architecture. Nice to have: Familiarity with SAP, BW, HANA, Tableau, or Power BI. Experience in auto, manufacturing, or supply chain industries. Certifications: AWS Certified Solution Architect, Databricks Certified Developer for Apache Spark.
