Associate Principal Engineer, Big Data

Summary

Join our Digital Product Engineering company as a Data Architect to lead the design and implementation of a self-service data architecture. You will empower business users to independently access, analyze, and derive insights from data. Responsibilities include designing a scalable and intuitive self-service architecture, selecting appropriate self-service analytics tools, establishing data governance and security measures, and developing and maintaining data models. You will also provide training and documentation, collaborate effectively, optimize performance, ensure data quality, support users, and drive continuous improvement. This role requires a Bachelor's or Master's degree in a related field, proven experience in designing self-service data solutions, strong knowledge of data architecture principles, and experience with self-service analytics tools. Excellent communication and problem-solving skills are essential.

Requirements

• Bachelor's or Master's degree in Computer Science, Information Technology, or a related field
• Proven experience as a Data Architect with a focus on designing self-service data solutions and empowering business users
• Strong knowledge of data architecture principles, data modeling, and database design concepts
• Experience with self-service analytics tools such as Tableau, Power BI, Qlik, or similar platforms
• Familiarity with data governance frameworks, data security practices, and compliance standards
• Proficiency in SQL and data manipulation languages for data querying and transformation
• Excellent communication skills, with the ability to translate technical concepts into user-friendly terms for business stakeholders
• Analytical mindset with the ability to analyze complex data requirements and translate them into actionable solutions
• Strong problem-solving skills

Responsibilities

• Data Architecture Design: Collaborate with business stakeholders, data engineers, and analysts to design a scalable and intuitive self-service data architecture that facilitates data discovery, exploration, and analysis
• Self-Service Tools Selection: Evaluate and recommend self-service analytics tools and platforms that align with the organization's goals and enable business users to access and manipulate data effectively
• Data Governance and Security: Establish data governance standards, access controls, and security measures to ensure data integrity, privacy, and compliance with regulatory requirements in the self-service model
• Data Modeling: Develop and maintain data models that support self-service analytics, ensuring data consistency, accuracy, and ease of use for business users
• Training and Documentation, Collaboration and Communication, Performance Optimization, Data Quality Assurance, User Support, Continuous Improvement