Lead Data Engineer
RIT Solutions
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 implementing AI based solutions within Data and Analytics platforms.
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