Senior Data Engineer

Martens is an iconic British brand founded in 1960 in Northamptonshire. Produced originally for workers looking for tough, durable boots, the brand was quickly adopted by diverse youth subcultures and associated musical movements. Martens has since transcended its working-class roots while still celebrating its proud heritage and, six decades later, “Docs” or “DM’s” are worn by people around the world who use them as a symbol of empowerment and their own individual attitude. The Company listed on the main market of the London Stock Exchange on 29 January 2021 (DOCS.Front-End Developer will play a crucial role in creating and optimising user interfaces to enhance the customer experience for digital commerce projects, including SAP Hybris Commerce and similar technologies. The developer will also identify opportunities for improving the performance and usability of web applications in a fast-paced, global digital commerce environment We are excited to announce an opening for Lead Data Engineer at Dr. Apache airflow, Airflow, Python, PySpark, SQLServer, SQL Scripting, SQL, DBT, SnowSQL, Snowflake, Azure Databricks, Azure DevOps, Terraform, Azure pipeline, Docker, Kubernetes Experience Range: ~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. 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. ~ With hands on experience on below technologies: ~ Python/ PySpark ~ SQL / SQL Scripting ~ Azure DevOps (Terraform , Azure pipeline , Docker , Kubernetes) ~ Snowflake 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., Understanding of data governance principles, quality frameworks, and security best practices. Experience with containerization and orchestration tools (e.g., Docker, Kubernetes) is a plus. Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field. Relevant certifications in data engineering or cloud technologies are a plus. Experience in the retail or fashion industry, with exposure to its data and analytics challenges. Familiarity with real-time data processing and streaming technologies. They never stand alone, but work together as a balancing act of rights and responsibilities to support how we work together at DMs. SHOW YOU CARE. Great relationship management that delivers results through effective teamwork You’ll 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