As the Senior Database Architect, you will provide technical leadership for the design, performance, scalability, and reliability of our production database environments. You will partner closely with Software Engineers, Platform Engineers, Product Managers, and other technical stakeholders to evaluate existing database architectures, identify opportunities for improvement, and establish database engineering best practices across our products.
A primary responsibility of this role is to optimize and maintain our high-volume OLTP databases, with a strong emphasis on PostgreSQL. You will assess existing environments, identify performance and scalability bottlenecks, and drive improvements across schema design, indexing, partitioning, query performance, replication, and database configuration. You will also provide guidance to engineering teams as they design and implement new database-backed features.
You will help strengthen production readiness by establishing and improving practices around performance testing, release validation, monitoring, alerting, backup and recovery, high availability, access controls, and incident response. You will play a key role in troubleshooting complex production issues, performing root-cause analysis, and ensuring database changes are thoroughly tested before deployment.
This role requires someone who can combine deep hands-on database expertise with strong technical judgment and communication skills and someone who can assess an existing environment, make practical recommendations, and partner with engineering teams to implement scalable, reliable solutions.
What You Need (Required Knowledge, Skills & Abilities):
- Education & Experience
- Bachelor's degree in Mathematics, Statistics, Computer Science, or related field
5+ years of experience as a Database Engineer, Data Engineer, or similar role
Core 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 architectures
Experience designing and implementing scalable data architectures, including batch and streaming pipelines
Experience building ELT pipelines with dbt and Snowflake
Intermediate to advanced Python development skills
Database Optimization & ReliabilityExperience assessing and improving existing database systems, including performance tuning (indexing, query optimization, partitioning) and data quality remediation
Strong understanding of database internals and transactional systems
Experience implementing backup, recovery, and high-availability strategies
Performance Testing & Release ValidationExperience designing and implementing performance/load testing frameworks for data systems
Knowledge of benchmarking, regression testing, and release validation processes
Experience building automated testing pipelines to ensure data quality and system performance across deployments
Production Operations & Data ReliabilityExperience defining and maintaining production database processes, including monitoring, alerting, and incident response
Familiarity with observability tools and practices (logging, metrics, tracing)
Strong understanding of SLAs, SLOs, and data reliability best practices
Tools & PlatformsExperience with AWS data technologies (Glue, Kinesis, Lambda)
Experience with orchestration tools (Airflow)
Experience with infrastructure-as-code (Terraform)
Knowledge of the Software Development Lifecycle
Preferred Skills & Experience:
Experience with CI/CD pipelines, especially for data systems
Experience with containerization (Docker, Kubernetes)
Knowledge of encryption, anonymization, and tokenization
Experience with open table formats and data catalogs
Familiarity with data observability tools (e.g., Monte Carlo, Datadog, Prometheus)
Who You Are (Soft Skills):
Detail-oriented, with a strong data quality mindset
Strong problem-solving and troubleshooting skills with a proactive approach to system reliability
Self-starter with a bias toward ownership and continuous improvement
Comfortable bringing structure and best practices to ambiguous or legacy environments
Thrives in a fast-paced, startup-oriented, team-focused culture
Positive, collaborative, and energetic attitude
Excellent verbal and written communication skills
Ability to clearly explain complex technical issues to both technical and non-technical audiences
Skills Required
- Bachelor's degree in Mathematics, Statistics, Computer Science, or a related field
- 5+ years of experience as a Database Engineer, Data Engineer, or similar role
- Experience designing, implementing, and maintaining high-performance, scalable OLTP systems
- Advanced SQL knowledge, including PostgreSQL and Snowflake
- Experience with data modeling, data warehouses, and lakehouse architectures
- Experience designing scalable data architectures with batch and streaming pipelines
- Experience building ELT pipelines with dbt and Snowflake
- Intermediate to advanced Python development skills
- Experience with database performance tuning, including indexing, query optimization, partitioning, and data quality remediation
- Strong understanding of database internals and transactional systems
- Experience implementing backup, recovery, and high-availability strategies
- Experience designing performance and load testing frameworks for data systems
- Knowledge of benchmarking, regression testing, and release validation processes
- Experience building automated testing pipelines for data quality and system performance
- Experience defining and maintaining production database processes, monitoring, alerting, and incident response
- Familiarity with observability tools and practices, including logging, metrics, and tracing
- Strong understanding of SLAs, SLOs, and data reliability practices
- Experience with AWS data technologies, including Glue, Kinesis, and Lambda
- Experience with orchestration tools such as Airflow
- Experience with infrastructure as code using Terraform
- Knowledge of the software development lifecycle
- Experience with CI/CD pipelines for data systems
- Experience with Docker and Kubernetes
- Knowledge of encryption, anonymization, and tokenization
- Experience with open table formats and data catalogs
- Familiarity with data observability tools such as Monte Carlo, Datadog, or Prometheus
What We Do
“Accelerate the digital transformation of your business with digital identity verification." Mitek (NASDAQ: MITK) is a global leader in mobile capture and digital identity verification solutions built on the latest advancements in AI and machine learning. Mitek’s identity verification solutions enable an enterprise to verify a user’s identity during a digital transaction, which assists financial institutions, payments companies and other businesses operating in highly regulated markets in mitigating financial risk and meeting regulatory requirements while increasing revenue from digital channels. Mitek also reduces the friction in the users’ experience with advanced data prefill and automation of the onboarding process. Mitek’s innovative solutions are embedded into the apps of more than 6,100 organizations and used by more than 80 million consumers for mobile check deposit, new account opening and more.








