About The Position

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.

Requirements

  • 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.

Nice To Haves

  • 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.

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.
© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service