We are seeking an experienced and highly skilled Lead Data Engineer to join our team and take ownership of complex data engineering projects. In this lead role, you will be responsible for the end-to-end implementation of data solutions focused on customer data across our systems. You will collaborate closely with Principal Architects, senior data engineers, and data stakeholders to drive the integration of customer-specific data from various source systems into our Customer Data Platform (CDP). As a hands-on architect and developer, you will lead data engineering teams to ensure data privacy, cybersecurity, and compliance with required approvals.

Key Responsibilities

1. Team Leadership & Project Ownership. Lead and mentor data engineering teams through all stages of design, development, and integration of secure, high-performance data solutions. Oversee the development of structured and unstructured data models, ensuring compliance with architectural and security guidelines.
2. Data Solution Design & Development. Review and enhance data solution designs to improve product quality and reduce risk. Implement innovative data engineering approaches and integrate new technologies into complex projects within the big data space.
3. Cross-Functional Collaboration. Partner with project teams to monitor progress, address issues, and represent data engineering requirements across all project phases. Work closely with cross-functional stakeholders to integrate data engineering insights into broader organizational projects and initiatives.
4. Data Governance & Quality Assurance. Maintain high levels of data integrity, utilizing data monitoring tools and overseeing mass data updates. Ensure that data operations align with business requirements, data privacy, and cybersecurity standards.
5. Coaching & Knowledge Sharing. Train and mentor business analytics users, enhancing their decision-making capabilities through robust data insights. Provide guidance and technical mentorship to junior data engineers, fostering growth and expertise within the team.
6. Relationship Building. Build and sustain strong relationships across the organization, acting as a central point of contact for complex data engineering and analytics solutions.

Required Qualifications & Experience

1. Education. Bachelor’s or Master’s degree in Computer Science, Information Technology, Software Engineering, Statistics/Mathematics, or a related field; equivalent work experience will also be considered.
2. Experience. 7-10 years in data analytics, data engineering, data modeling, or related fields, with a proven track record in data pipeline development, ETL, and data warehousing.

Technical Skills

1. Must-Have. Proficiency in SQL, Python, and experience with Azure Data Lake Storage (ADLS) and Azure Data Factory (ADF), AWS.
2. Preferred Knowledge. Power BI, ThoughtSpot for data visualization and analysis.
3. Core Competencies. Data engineering, data analysis, data modeling, and data warehousing expertise.
4. Programming Languages. Experience with Java and Scala for scalable data solutions.
5. ETL Development. Strong knowledge in Extract, Transform, Load (ETL) processes for effective data pipeline implementation.

Cross-Organizational Skills

1. Communication. Effective communicator with the ability to explain complex technical concepts to diverse stakeholders.
2. Results-Driven. Proven focus on achieving business outcomes and delivering impactful results.
3. Learning Agility. Adaptable to new technologies and data engineering innovations.
4. Customer-Centric Approach. Deep understanding of customer needs and a focus on enhancing data-driven business insights.

Impact & Scope

This role offers the opportunity to collaborate with other lead engineers in driving customer data through our CDP, ensuring all business requirements are met while upholding privacy and cybersecurity standards. As a Lead Data Engineer, your contributions will be essential in enabling data-driven decision-making across the organization.