Lead Data Engineer

Job Title:

Primary Skill:

Type of Work:

Working Hours:

Resource Experience (in years):6- 12

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.

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

Airflow

DBT or SnowSQL

Azure DevOps (Terraform , Azure pipeline , Docker , Kubernetes)

Snowflake Good to have

Azure Databricks

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:

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.

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