Senior Data Architect

Job Details

Location:

ATLANTA, GA 30324

Position Type:
Full Time

Education Level: Not Specified

Salary Range: $ - $ Salary/year

Travel Percentage:
None

Job Category:
Engineering

Company:
Coreforce

Location:

Atlanta

Job Type: Full-time

Salary:
Based on Experience

Coreforce is an innovative SaaS company providing digital solutions for frontline professionals. Our products, body cameras, in-car videos, mobile routers, and digital evidence systems help public safety officers and first responders save lives, strengthen community trust, and enhance accountability.

Join Coreforce and use your data architect skills to support innovative technology that strengthens communities.

• Flexible hybrid schedule
• Free chef-inspired lunch Mon–Thu
• Competitive benefits: medical, dental, vision, 401(k). We provide 401(k) matching per the terms of the 401(k) plan.
• 15 PTO days + floating holiday
• Annual bonus and tuition reimbursement
• Career growth in a fast-growing, mission-driven company
• Collaborative, purpose-driven culture

• Define scalable, canonical data models that support product capabilities, integrations, analytics, reporting, and AI-enabled use cases.
• Establish enterprise data modeling standards, naming conventions, domain models, schema design practices, and data lifecycle patterns.
• Translate business and product requirements into durable logical and physical data models across operational and analytical systems.
• Guide engineering teams in designing consistent data contracts, entity relationships, event structures, streaming data models, metadata models, and integration patterns.

• Architect solutions using MySQL, PostgreSQL, MongoDB, and other structured, semi-structured, and unstructured data stores.
• Design and govern caching strategies using Redis or similar caching technologies to improve application performance and scalability.
• Evaluate and recommend appropriate database, storage, indexing, partitioning, replication, and archival strategies based on workload characteristics
• Support hybrid data architectures spanning transactional databases, document stores, object storage, search systems, data warehouses, and reporting platforms.

• Design and govern streaming data architectures that support real-time ingestion, event processing, analytics, operational workflows, and downstream integrations.
• Define standards for event schemas, message contracts, topic design, partitioning, ordering, retention, replay, dead-letter handling, and consumer resiliency.
• Partner with engineering teams to evaluate and implement streaming platforms and patterns such as Kafka, Amazon Kinesis, or comparable event streaming technologies.
• Ensure streaming data pipelines meet requirements for scalability, reliability, observability, security, compliance, latency, and data quality.

• Lead database optimization efforts including query tuning, indexing strategy, schema refinement, storage layout, and performance troubleshooting.
• Perform capacity planning for data platforms, accounting for growth, retention, throughput, latency, concurrency, and cost.
• Define standards for observability, monitoring, alerting, backup, recovery, high availability, and disaster recovery for critical data stores.
• Partner with engineering and operations teams to improve reliability, scalability, and cost efficiency of production data systems.

• Design and support data warehousing architectures that enable reliable analytics, operational reporting, compliance reporting, and executive dashboards.
• Develop dimensional, normalized, and hybrid models appropriate for BI reporting solutions and analytical workloads.
• Work with stakeholders to ensure data pipelines, marts, semantic layers, and reporting datasets are accurate, governed, and understandable.
• Establish patterns for data quality, lineage, governance, cataloging, retention, and access control across reporting and analytical platforms.