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About the Role
Tribal Tech - The Digital, Data & AI Specialists is seeking an exceptional Lead Data Engineer to join their innovative team. This role offers a unique opportunity to shape the future of data-driven decision-making within a rapidly growing organization.
Key Responsibilities
- Design and implement complex data flows to connect operational systems, data for analytics, and business intelligence (BI) systems
- Lead the development and maintenance of data-streaming systems
- Coordinate teams and set best practices and standards for data engineering
- Manage and optimize data architecture, ensuring data quality, scalability, and security
- Provide technical guidance and mentorship to a team of data engineers
- Collaborate with data scientists, analysts, and business stakeholders to support data-driven initiatives
- Champion data engineering best practices across the organization
Requirements
- 8+ years of work experience, with at least 2 years in a similar role
- Strong expertise in data architecture, data quality, metadata management, ETL processes, and database administration
- Proficiency in SQL and modern programming languages (preferably Python)
- Extensive experience with cloud platforms (AWS, Azure, or GCP) and big data technologies (e.g., Hadoop, Spark, Kafka)
- Solid understanding of data modeling techniques and best practices
- Experience in designing and implementing data warehousing solutions
- Strong problem-solving abilities and excellent communication skills
- Proven track record of leading and mentoring data engineering teams
Preferred Qualifications
- Experience with data streaming architectures and real-time processing
- Knowledge of e-commerce data structures and analytics
- Familiarity with CI/CD practices and DevOps principles
- Relevant certifications (e.g., AWS Certified Data Analytics, Azure Data Engineer Associate)
This is an excellent opportunity for a talented Lead Data Engineer to make a significant impact in a dynamic, fast-paced e-commerce environment. You will play a crucial role in shaping the data infrastructure and driving data-driven decision-making across the organization.