Principal Data and Analytics Engineer- Remote US – USA Remote Jobs
Principal Data and Analytics Engineer – Remote (United States) Location: 100% Remote (U.S. Based) Employment Type: Full-Time Experience Level: Principal / Senior Department: Data Engineering / Analytics About the Company Our client is a leading technology-driven organization specializing in data intelligence, cloud analytics, and digital transformation . The company partners with Fortune 500 enterprises to deliver end-to-end data engineering solutions, from real-time analytics to AI-driven insights. Recognized for its innovative data culture and collaborative remote-first environment , the company empowers employees to solve complex problems using cutting-edge tools in cloud, big data, and machine learning ecosystems. They are now seeking a Principal Data and Analytics Engineer to lead architectural design, mentor engineering teams, and drive enterprise-level data strategy initiatives. Position Overview As the Principal Data and Analytics Engineer , you will be responsible for architecting, designing, and implementing scalable data platforms and analytical solutions. This role will serve as a key technical leader, influencing data architecture standards, promoting best practices, and ensuring alignment between data strategy and business outcomes. You’ll collaborate with cross-functional teams—including data scientists, analysts, and software engineers—to build advanced data systems that enable decision-making at scale. Key Responsibilities Design, develop, and optimize large-scale data pipelines and architectures for structured and unstructured data. Lead the development of cloud-based data platforms (AWS, Azure, or GCP). Establish best practices for data modeling, ETL/ELT processes, data governance, and quality. Partner with business stakeholders to understand analytical needs and translate them into technical solutions. Architect data warehouse and data lake solutions to support real-time and batch analytics. Collaborate with DevOps to automate deployment, monitoring, and scaling of data systems. Drive innovation through modern data frameworks such as Spark, Databricks, Snowflake, or BigQuery. Mentor junior and mid-level engineers on coding, architecture, and design principles. Lead data infrastructure projects from conception to deployment with a focus on scalability and reliability. Stay up-to-date with emerging trends in data engineering and analytics technologies. Qualifications & Experience Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field. 8–12 years of experience in data engineering, business intelligence, or analytics. Proven expertise in data architecture, data modeling, and pipeline design . Strong hands-on experience with: Cloud platforms: AWS (Glue, Redshift, S3), Azure (Synapse), or GCP (BigQuery). Data frameworks: Apache Spark, Databricks, Airflow, Kafka, or Snowflake. Programming languages: Python, SQL, Scala, or Java. Experience with CI/CD pipelines and containerization (Docker, Kubernetes). Familiarity with data governance, security, and compliance best practices. Strong problem-solving, analytical, and communication skills. Proven ability to work collaboratively in distributed remote teams. Preferred Skills Experience with ML model deployment and MLOps pipelines. Knowledge of APIs and microservices for data integration. Familiarity with BI and visualization tools (Tableau, Power BI, Looker). Prior experience in leading or architecting enterprise-scale data modernization projects. What the Company Offers Competitive base salary + annual performance bonus. Full benefits package (medical, dental, vision, and life insurance). 401(k) with employer match. 100% remote work flexibility across the U.S. Generous PTO and paid holidays. Professional development stipends and certification sponsorships. Inclusive, collaborative, and innovation-focused work culture. This is an outstanding opportunity for a senior-level data engineering professional to lead strategic data initiatives, architect enterprise solutions, and influence the future of analytics in a forward-thinking, remote-first organization.