Lead Data Engineer

SO, WHAT'S THE STORY? As a Lead Data Engineer, you will play a key role in the development and maintenance of the organization's data infrastructure. Working within a multi-disciplined team led by the Senior Manager - Data Engineer, you will focus on building and optimizing scalable data pipelines and supporting the delivery of high-quality, reliable data solutions. This is an exciting opportunity to contribute to a dynamic and innovative environment, where your work will directly impact the organization's ability to harness data for analytics, reporting, and decision-making. THE GIG As a Lead Data Engineer, you will: Develop and maintain scalable data pipelines to support operational and analytical needs. Collaborate with data scientists, analysts, and business teams to understand data requirements and deliver solutions that align with organizational goals. Optimize and maintain cloud-based data infrastructure (e.g., Snowflake, Azure) for performance and cost-efficiency. Ensure the integrity, reliability, and security of data through robust testing and validation practices. Support the implementation of data governance practices, working closely with the Data QA Specialist and Data Governance Lead. Monitor and troubleshoot data pipeline performance issues, proactively resolving bottlenecks and incidents. Contribute to the design and implementation of data models and schemas that meet business requirements. Stay updated on emerging technologies and best practices, recommending improvements to existing processes and tools. THE STUFF THAT SETS YOU APART Must-Have Experience: 6+ years of experience in data engineering or a similar role. Hands-on experience building and maintaining data pipelines, ETL processes, and integrations. Proficiency in programming languages commonly used in data engineering (e.g., Python, SQL, Scala). Experience with cloud data platforms such as Snowflake or Azure. Solid understanding of data modelling principles and database management systems. Technical Skills: Knowledge of big data frameworks and processing tools (e.g., Snowflake, dbt, Apache Spark, Hadoop). Familiarity with DevOps practices, including CI/CD pipelines and version control systems (e.g., Git). Understanding of data governance principles, quality frameworks, and security best practices. Experience with containerization and orchestration tools (e.g., Docker, Kubernetes) is a plus. Soft Skills: Strong problem-solving skills with attention to detail. Excellent communication and collaboration skills, with the ability to work effectively within a team. A proactive attitude, with a willingness to learn and take ownership of tasks. Education: Bachelors degree in Computer Science, Data Engineering, Information Systems, or a related field. Relevant certifications in data engineering or cloud technologies are a plus. Nice to Have: Experience in the retail or fashion industry, with exposure to its data and analytics challenges. Familiarity with real-time data processing and streaming technologies. Knowledge of DataOps principles and practices. We live and breathe Rebellious Self Expression at Dr. Martens, and there are 3 core values at the heart of it. They never stand alone, but work together as a balancing act of rights and responsibilities to support how we work together at DMs. BE YOURSELF. ACT COURAGEOUSLY. SHOW YOU CARE. At DM your technical capability will go hand in hand with the below: Great relationship management that delivers results through effective teamwork Youll be a proud custodian to our DMs culture, embodying what we stand for and encouraging others to do the same Youll help build a highly engaged team ensuring a collaborative culture and providing guidance & support to other team members You will take ownership for your own development, proactively seeking out feedback to build self-awareness You will bring the outside-in; youll share best practice across the team/business and encourage ideas sharing as well as collaborative problem solving Youll lead the way and role model on all things DE&I & wellbeing