As the Sr. Data Engineer - Architecture, you will drive data infrastructure that enables data-informed decision-making, applying modern engineering and distributed systems practices. You will partner closely with Product Managers, Data Analysts, Software Engineers, and business stakeholders to deliver stable, high-quality data pipelines, enterprise reporting, and datasets that support analytics and machine learning use cases.A primary responsibility of this role is to optimize and maintain our OLTP databases, ensuring reliability, performance, and production readiness. This includes auditing systems, improving data quality, refactoring legacy pipelines, and applying best practices for schema design, indexing, and query performance. In parallel, you will build and maintain scalable data systems that power advanced analytics across the business.You will design performance testing and release validation frameworks to prevent regressions and ensure data integrity, while establishing strong production processes such as monitoring, alerting, backup and recovery, access controls, and incident response.What You Need (Required Knowledge, Skills & Abilities):Education & ExperienceBachelor's degree in Mathematics, Statistics, Computer Science, or related field5+ years of experience as a Database Engineer, Data Engineer, or similar roleCore Data Engineering & ArchitectureExperience designing, implementing, and maintaining high performant, scalable OLTP systems.Hands-on experience and advanced knowledge of SQL (e.g., Postgres, Snowflake)Strong experience with data modeling, data warehouses, and lakehouse architecturesExperience designing and implementing scalable data architectures, including batch and streaming pipelinesExperience building ELT pipelines with dbt and SnowflakeIntermediate to advanced Python development skillsDatabase Optimization & ReliabilityExperience assessing and improving existing database systems, including performance tuning (indexing, query optimization, partitioning) and data quality remediationStrong understanding of database internals and transactional systemsExperience implementing backup, recovery, and high-availability strategiesPerformance Testing & Release ValidationExperience designing and implementing performance/load testing frameworks for data systemsKnowledge of benchmarking, regression testing, and release validation processesExperience building automated testing pipelines to ensure data quality and system performance across deploymentsProduction Operations & Data ReliabilityExperience defining and maintaining production database processes, including monitoring, alerting, and incident responseFamiliarity with observability tools and practices (logging, metrics, tracing)Strong understanding of SLAs, SLOs, and data reliability best practicesTools & PlatformsExperience with AWS data technologies (Glue, Kinesis, Lambda)Experience with orchestration tools (Airflow)Experience with infrastructure-as-code (Terraform)Knowledge of the Software Development LifecyclePreferred Skills & Experience:Experience with CI/CD pipelines, especially for data systemsExperience with containerization (Docker, Kubernetes)Knowledge of encryption, anonymization, and tokenizationExperience with open table formats and data catalogsFamiliarity with data observability tools (e.g., Monte Carlo, Datadog, Prometheus)Who You Are (Soft Skills):Detail-oriented, with a strong data quality mindsetStrong problem-solving and troubleshooting skills with a proactive approach to system reliabilitySelf-starter with a bias toward ownership and continuous improvementComfortable bringing structure and best practices to ambiguous or legacy environmentsThrives in a fast-paced, startup-oriented, team-focused culturePositive, collaborative, and energetic attitudeExcellent verbal and written communication skillsAbility to clearly explain complex technical issues to both technical and non-technical audiencesWe are proud to offer competitive salary ranges aligned to industry standards. Please note that our ranges are representative and individual compensation specifics may vary based upon experience level, professional competencies and geographic differentials.We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
