What are the responsibilities and job description for the Principal Data Engineer position at Eucloid Data Solutions?
Job Description
We are seeking a talented and driven Data Engineer with expertise in Databricks to join our team in USA. The ideal candidate is passionate about building data platforms, designing scalable solutions, and working in modern cloud-native environments. As a Data Engineer at Eucloid, you will play a key role in developing and optimizing robust data architectures using Databricks Lakehouse Platform, while collaborating with cross-functional teams to drive impactful analytics and machine learning outcomes for our clients.
Responsibilities
• Serve as the primary technical lead and trusted advisor for the client's Databricks platform, data engineering initiatives, and enterprise reporting ecosystem.
• Partner with business and technology stakeholders to define data platform strategy, architecture roadmap, and scalable analytics solutions aligned with business goals.
• Design, develop, and oversee implementation of high-performance ETL/ELT pipelines, Lakehouse architectures, and data products using Databricks, PySpark, SQL, and cloud native technologies.
• Drive platform reliability, scalability, security, governance, data quality, and cost optimization through engineering best practices and architectural oversight.
• Lead and mentor data engineering teams, establish development standards, conduct design reviews, and promote a culture of engineering excellence.
• Collaborate with business users, analysts, reporting teams, and data scientists to deliver reliable, production-ready data and reporting solutions.
Background & Skills
• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative discipline.
• 10 years of experience in Data Engineering, Data Warehousing, and Cloud Data Platforms.
• 4 years of hands-on experience designing and implementing solutions on Databricks.
• Strong expertise in Databricks, PySpark, Spark SQL, Delta Lake, Unity Catalog, and Lakehouse architecture.
• Proven experience building and managing large-scale data platforms on AWS, Azure, or GCP.
• Proficiency in Python, PySpark, SQL, and data modeling for enterprise-scale data solutions.
• Hands-on experience with Airflow, dbt, Terraform, Kafka, Databricks Workflows, and Delta Live Tables.
• Strong stakeholder management, communication, and team leadership skills; Databricks and/or Cloud certifications are preferred.