Database Architect

As a Data Platform / Database Architect at the company, your role will involve owning the end-to-end design and performance of the data platform. You will be responsible for designing multi-tenant Postgres schemas, optimizing Postgres performance, building event-streaming with Kafka/Debezium, modeling analytics layers, ensuring data security, integrating AI plumbing, establishing observability, and collaborating with other teams within the company. **Key Responsibilities:** - Design multi-tenant Postgres schemas including partitioning, indexing, normalization, and RLS. Define retention and archival strategies. - Optimize Postgres performance by utilizing EXPLAIN/ANALYZE, connection pooling, vacuum/bloat control, query/index tuning, and replication. - Build event-streaming/CDC with Kafka/Debezium, manage topics, partitions, schema registry, and deliver data to ClickHouse/Snowflake/BigQuery. - Model analytics layers, orchestrate jobs with Airflow/Dagster, and implement transformations using dbt. - Establish observability and SLOs for data by monitoring query/queue metrics, tracing, alerting, and capacity planning. - Implement data security measures including encryption, masking, tokenization of PII, IAM boundaries, and contribute to audit posture. - Integrate AI plumbing such as vector embeddings, feature store patterns, retrieval pipelines, and metadata lineage. - Collaborate with backend/ML/product teams to review designs, coach engineers, document processes, and lead migrations. **Qualifications Required:** - Minimum 6 years of experience in building high-scale data platforms with expertise in PostgreSQL. - Hands-on experience with Kafka, Debezium, and CDC patterns. Familiarity with schema registry and analytics engines like ClickHouse, Snowflake, or BigQuery. - Proficiency in Python, data tooling libraries, orchestration tools like Airflow, and transformations with dbt. - Strong cloud experience in AWS/GCP/Azure, including networking, security groups/IAM, secrets management, and cost controls. - Performance engineering mindset, excellent communication skills, and documentation abilities. The job also mentions some nice-to-have qualifications, such as experience with vector/semantic search, feature store, RAG data pipelines, fintech-style domains, infra-as-code, containerized services, observability stacks, exposure to Go/Java, and proficiency in Lakehouse formats. As a Data Platform / Database Architect at the company, your role will involve owning the end-to-end design and performance of the data platform. You will be responsible for designing multi-tenant Postgres schemas, optimizing Postgres performance, building event-streaming with Kafka/Debezium, modeling analytics layers, ensuring data security, integrating AI plumbing, establishing observability, and collaborating with other teams within the company. **Key Responsibilities:** - Design multi-tenant Postgres schemas including partitioning, indexing, normalization, and RLS. Define retention and archival strategies. - Optimize Postgres performance by utilizing EXPLAIN/ANALYZE, connection pooling, vacuum/bloat control, query/index tuning, and replication. - Build event-streaming/CDC with Kafka/Debezium, manage topics, partitions, schema registry, and deliver data to ClickHouse/Snowflake/BigQuery. - Model analytics layers, orchestrate jobs with Airflow/Dagster, and implement transformations using dbt. - Establish observability and SLOs for data by monitoring query/queue metrics, tracing, alerting, and capacity planning. - Implement data security measures including encryption, masking, tokenization of PII, IAM boundaries, and contribute to audit posture. - Integrate AI plumbing such as vector embeddings, feature store patterns, retrieval pipelines, and metadata lineage. - Collaborate with backend/ML/product teams to review designs, coach engineers, document processes, and lead migrations. **Qualifications Required:** - Minimum 6 years of experience in building high-scale data platforms with expertise in PostgreSQL. - Hands-on experience with Kafka, Debezium, and CDC patterns. Familiarity with schema registry and analytics engines like ClickHouse, Snowflake, or BigQuery. - Proficiency in Python, data tooling libraries, orchestration tools like Airflow, and transformations with dbt. - Strong cloud experience in AWS/GCP/Azure, including networking, security groups/IAM, secrets management, and cost controls. - Performance engineering mindset, excellent communication skills, and documentation abilities. The job also mentions some nice-to-have qualifications, such as experience with vector/semantic search, feature store, RAG data pipelines, fintech-style domains, infra-as-code, containerized services, observability stacks, exposure to Go/Java, and proficiency in Lakehouse formats.