Principal Data Engineer

About the role

In this vital role you will lead the design, development, and implementation of our data strategy. The ideal candidate possesses a deep understanding of data engineering principles, coupled with strong leadership and problem-solving skills. As a Principal Data Engineer, you will architect and oversee the development of robust data platforms, while mentoring and guiding a team of data engineers.

Responsibilities

• Lead the design, development, and implementation of the data strategy.
• Possess strong rapid prototyping skills and quickly translate concepts into working code.
• Provide expert guidance and mentorship to the data engineering team, fostering a culture of innovation and best practices.
• Design, develop, and implement robust data architectures and platforms to support business objectives.
• Oversee the development and optimization of data pipelines and data integration solutions.
• Establish and maintain data governance policies and standards to ensure data quality, security, and compliance.
• Architect and manage cloud-based data solutions, leveraging AWS or other preferred platforms.
• Lead and motivate a high-performing data engineering team to deliver exceptional results.
• Identify, analyze, and resolve complex data-related challenges.
• Collaborate closely with business stakeholders to understand data requirements and translate them into technical solutions.
• Stay abreast of emerging data technologies and explore opportunities for innovation.

Requirements

Functional Skills

• Must-Have Skills:
  • Demonstrated proficiency in leveraging cloud platforms (AWS, Azure, GCP) for data engineering solutions.
  • Strong understanding of cloud architecture principles and cost optimization strategies.
  • Proficient in Python, PySpark, SQL.
  • Hands-on experience with big data ETL performance tuning.
  • Proven ability to lead and develop high-performing data engineering teams.
  • Strong problem-solving, analytical, and critical thinking skills to address complex data challenges.
• Good-to-Have Skills:
  • Experience with data modeling and performance tuning for both OLAP and OLTP databases.
  • Experience with Apache Spark, Apache Airflow.
  • Experience with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven, etc.), automated unit testing, and DevOps.
  • Experience with AWS, GCP or Azure cloud services.

Education and Professional Certifications

• Doctorate degree and 2 years of Data Engineer experience
• OR Masters degree and 4 years of Data Engineer experience
• OR Bachelors degree and 6 years of Data Engineer experience
• OR Associates degree and 10 years of Data Engineer experience
• OR High school diploma / GED and 12 years of Data Engineer experience
• AWS Certified Data Engineer preferred
• Databricks Certificate preferred

Soft Skills

• Excellent analytical and troubleshooting skills.
• Strong verbal and written communication skills.
• Ability to work effectively with global, virtual teams.
• High degree of initiative and self-motivation.
• Ability to manage multiple priorities successfully.
• Team-oriented, with a focus on achieving team goals.
• Strong presentation and public speaking skills.