Job Description

We're looking for a Lead Data Engineer to own the design and evolution of our modern data platform at Catalyst Brands, powering data-driven decisions across our portfolio of retail and consumer brands. You'll lead complex, high-impact data initiatives using AWS, Snowflake/Redshift, Spark, and modern orchestration and governance tools to build scalable, reliable, and trusted data products. This role blends hands-on technical expertise with architecture ownership and cross-functional leadership, partnering closely with product, analytics, and business stakeholders to unlock new insights, optimize performance, and enable the next generation of data and analytics solutions.

Primary Responsibilities:

• Lead the design and delivery of scalable, secure, and reliable data pipelines and platforms.
• Define and enforce data engineering standards, best practices, and architecture patterns.
• Partner with business, product, analytics, and data science teams to translate requirements into technical solutions.
• Drive performance, scalability, and cost optimization across data infrastructure.
• Establish data governance, quality, security, and compliance practices.
• Own code quality through mandatory design and code reviews.
• Lead cross-functional data initiatives and provide technical direction across teams.
• Mentor and coach data engineers, fostering a culture of engineering excellence and continuous improvement.

Basic Qualifications

• Bachelor's degree in computer science, engineering or related field with 8+ years of data engineering experience.
• Strong programming skills in Python and/or PySpark.
• Experience with cloud data warehouses like Snowflake and Redshift.
• Strong knowledge of AWS services, including S3, EC2, EMR, Glue, Athena, Lambda, and CloudWatch.
• Expertise in Apache Spark or similar distributed data processing engines.
• Experience with following tools Apache Airflow, DBT, GitLab, CI/CD pipelines, Docker, and Kubernetes.
• Strong SQL and data modeling experience.
• Experience mentoring engineers and influencing technical direction across multiple teams.
• Excellent communication skills with the ability to translate business requirements into complex technical solutions.

Preferred Qualifications

• Master's degree in computer science, Engineering, Data Science, or a related field.
• Experience in a lead/architect role within data engineering teams.
• Knowledge of data streaming services like Apache Kafka.
• Experience with Data Governance tools like Great Expectations and DataHub.
• Experience implementing and scaling data governance frameworks, including metadata management and data cataloging.
• Experience in high-volume retail, e-commerce, or consumer-facing environments.
• Familiarity with cost optimization techniques for cloud data platforms.
• Familiarity of impleting AI based solutions within Data and Analytics platforms.

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