Senior Data Engineer, Rebrandly

• You're an experienced data engineer who thrives in fast-paced scale-up environments where you can make an immediate impact
• You excel at working independently, making architectural decisions, and building robust data systems from scratch
• You have deep expertise in AWS data technologies, particularly Redshift and DynamoDB, and understand how to leverage these tools to build scalable, performant data infrastructure
• You're passionate about not just collecting and storing data, but actively pushing insights back into business operations through reverse ETL processes
• You have strong communication skills that enable you to collaborate effectively in a remote distributed team environment, with the ability to clearly articulate technical concepts to both technical and non-technical stakeholders
• You excel at independent project management and take full ownership of deliverable timelines, ensuring commitments are met while balancing multiple priorities
• 5+ years of hands-on experience with AWS Redshift, including performance optimization, cluster management, and advanced SQL
• 3+ years working with AWS RDS, DynamoDB and NoSQL data modeling patterns
• Proven experience building reverse ETL pipelines and data activation frameworks
• Strong Python or similar programming skills for data pipeline development
• Experience as a solo data engineer or leading data initiatives independently
• Track record of building data infrastructure in scale-up environments (Series A-C)
• Expertise in modern data stack tools (dbt, Airflow, Census, Fivetran, or similar)
• Experience with streaming data architectures and real-time analytics
• Deep understanding of data warehouse design patterns and dimensional modeling
• Proficiency in Infrastructure as Code (Terraform preferred) for AWS resources
• Strong written and verbal communication skills with proven ability to work effectively in remote distributed teams
• Demonstrated experience in independent project management with a track record of owning and delivering complex data projects on schedule
• Previous experience working in SaaS companies with an understanding of SaaS-specific data challenges and metrics
• Advanced SQL and query optimization techniques
• Experience with CDC (Change Data Capture) patterns
• API development for data services (REST/GraphQL)
• Data quality frameworks and monitoring
• Cost optimization strategies for AWS data services
• Experience with data cataloging and metadata management
• Experience with SaaS-specific data patterns including multi-tenancy, subscription analytics, and usage-based metrics
• AI-First Mindset with solving data engineering challenges
• Comfortable with ambiguity and rapid change
• Ability to deliver MVPs quickly while planning for scale
• Experience wearing multiple hats in lean teams
• Strong business acumen and understanding of SaaS metrics
• Self-directed with excellent prioritization skills

Desirable

• As our Senior Data Engineer, you will be the sole architect and enabler of our entire data ecosystem in a dynamic scale-up environment. This is a unique opportunity to build and own our data infrastructure from the ground up, with a strong focus on AWS technologies, particularly Redshift, DynamoDB, RDS
• You'll design and implement sophisticated data pipelines, including reverse ETL processes that push insights back into our operational systems, directly impacting how we serve millions of users globally
• In this high-impact role, you'll work autonomously while collaborating closely with product, engineering, and growth teams. Your work will be the foundation for data-driven decision-making across the entire organization, with direct visibility to leadership and meaningful influence on company strategy
• Serve as the sole data engineer responsible for architecting, building, and maintaining our complete data infrastructure
• Make critical architectural decisions that will shape our data strategy for years to come
• Build a robust data platform that scales with our rapid growth from tens of thousands to millions of users
• Design and optimize our AWS Redshift data warehouse as the central hub for analytics
• Implement efficient data ingestion from AWS RDS, AWS DynamoDB and other NoSQL sources
• Leverage AWS services (Lambda, Glue, Kinesis, S3) to create a modern data stack
• Optimize query performance and manage Redshift cluster scaling strategies
• Build sophisticated reverse ETL pipelines to operationalize insights
• Push enriched data back to production systems, CRM, marketing automation, and customer success tools
• Create real-time data activation frameworks that enhance user experiences
• Design feedback loops that enable data-driven product features
• Rapidly prototype and deploy data solutions to support aggressive growth targets
• Balance speed with reliability in a fast-moving environment
• Build self-service analytics capabilities to empower teams across the organization
• Establish data governance practices that scale with minimal overhead
• Define data engineering best practices and standards for the organization
• Mentor other engineers on data concepts and AWS technologies
• Partner with stakeholders to translate business needs into technical solutions
• Champion data quality and reliability across all systems