Data Engineering Team Lead

Job Description

THE DEPARTMENT:
The Information Technology Department is responsible for the establishment and maintenance of a secure technology infrastructure to support the Product, People, Promotion, Place and Profit areas of Helzberg Diamonds. It accomplishes this through the design, development and deployment of automated systems to meet the information and process needs of each major line of business: human resources, merchandise, marketing, finance, stores, and E-Commerce. In addition to these lines of business applications, the IT organization is responsible for the collection and correlation of all company electronic information assets into an enterprise Data Warehouse which is used to support the overall analytical and reporting information needs of the business.

POSITION SUMMARY:
The Data Engineering Team Lead will play a critical role in advancing Helzberg Diamonds' data strategy by leading the design, development, and operation of scalable, reliable data platforms and pipelines. This role blends hands-on technical leadership with people management, serving as both a technical authority and a coach for a growing data engineering team. The ideal candidate is passionate about building high-quality data products, enabling analytics and AI use cases, and partnering closely with business and technology stakeholders across eCommerce, Marketing, Merchandising, Finance, and Operations.


PRINCIPAL ACCOUNTABILITIES:
Technical Leadership

• Lead the design and implementation of modern data engineering solutions, including data ingestion, transformation, and orchestration pipelines.
• Own and evolve core data platforms such as the enterprise data warehouse/lakehouse, ensuring scalability, reliability, and performance.
• Establish and enforce engineering best practices for data modeling, code quality, testing, monitoring, and documentation.
• Partner with architecture, security, and infrastructure teams to ensure solutions meet enterprise standards for availability, security, and compliance.

Team Leadership & People Development

• Lead, mentor, and grow a team of data engineers, fostering a culture of accountability, learning, and continuous improvement.
• Provide technical guidance, code reviews, and career development support for team members.
• Assist with hiring, onboarding, and performance management of data engineering talent.

Delivery & Stakeholder Collaboration

• Collaborate closely with Analytics, Data Science, Product, and Business teams to translate business requirements into scalable data solutions.
• Prioritize work in partnership with stakeholders, balancing near-term delivery with long-term platform health.
• Support data governance, data quality, and master data initiatives to ensure trusted, business-ready data.

Operational Excellence

• Ensure reliable operation of data pipelines through monitoring, alerting, and incident response.
• Drive improvements in data observability, cost optimization, and platform efficiency.
• Contribute to roadmap planning and data strategy discussions at the program and portfolio level.

SUPERVISORY RESPONSIBILITIES:
This position supervises a team of 2-3 Data Warehouse Analysts and Engineers and will be responsible for the following:

• Accomplish department objectives by directing and monitoring the work progress of direct report.
• Provide coaching and guidance to direct report.
• Set expectations, annual goals and provide required quarterly touch base meetings with all direct report.

QUALIFICATIONS:
Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field (or equivalent experience).
• 7+ years of experience in data engineering, software engineering, or related roles.
• 2+ years of experience in a technical leadership or team lead role.
• Strong experience with SQL and data modeling for analytics and reporting.
• Hands-on experience building and operating data pipelines using modern tools and frameworks (e.g., cloud-native services, ELT/ETL platforms, orchestration tools).
• Proficiency in at least one programming language commonly used in data engineering (e.g., Python, Scala, or Java).

Preferred Qualifications

• Experience with cloud data platforms (e.g., Snowflake, Databricks, BigQuery, Redshift, or equivalent).
• Experience supporting retail, eCommerce, or omnichannel data use cases.
• Familiarity with CI/CD, Infrastructure as Code, and DevOps practices in a data engineering context.
• Experience working with streaming or near-real-time data.
• Strong communication skills with the ability to influence both technical and non-technical stakeholders.

Work Schedule:
Hybrid schedule with predictable onsite attendance required three or more days per week to perform essential functions involving interactive behaviors with co-workers and managers, operation or manipulation of equipment and/or materials located only on site, and direct interaction with internal and/or external customers.


COMPETENCIES:
Analytical Thinking, Customer Service Orientation, Integrity, Teamwork and Cooperation