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About
Lead Data Engineer Location:
95% remote with travel to Dallas 4 times per year - Travel will be covered by the client
candidates who live in EST or CST to be considered for remote.
Please let me know if you have any candidates that we can submit who are ok with travel to Dallas 4x per year and then can work remote.
We are needing candidates who have hands on experience in
Amazon RedShift , this is a must have.
Lead Data Engineer, Technology | Data & Analytics
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.
Languages
- English
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