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From Home Clinical Database Programmer Jobs in Texas

... from traditional DBA operations to an AI-first Database Platform Engineering model. • Drive AI-powered automation for database provisioning, monitoring, maintenance, performance tuning, and ...

Oracle Database Administrator (DBA)

San Antonio, TX · On-site

$46.25 - $62.75/hr

SIMILAR CAREER TITLES Database Administrator, Oracle Developer, SQL Database Administrator, Data ... From employee and family events to career-long support, we create a community you'll never want to ...

Lead Database Engineering

Dallas, TX · On-site +1

$120K - $160K/yr

From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are ...

Lead Database Engineering

Dallas, TX · On-site

$120K - $160K/yr

From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are ...

Lead Database Engineering

Dallas, TX · On-site +1

$120K - $160K/yr

From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are ...

Oracle DBA (Database Administrator)

San Antonio, TX · On-site

$46.25 - $62.75/hr

... Database Engineer, Data Warehouse Administrator, Oracle Systems Analyst, Cloud Database ... From employee and family events to career-long support, we create a community you'll never want to ...

Lead Database Engineering

Dallas, TX · On-site

$120K - $160K/yr

From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are ...

Database Administrator IV

Austin, TX · On-site

$84K - $113K/yr

Participates in agile data engineering development and supports database design and implementation ... Bachelor's Degree from accredited university in Computer Science, Management Information Systems ...

Showing results 41-60

From Home Clinical Database Programmer information

What is the difference between From Home Clinical Database Programmer vs On-Site Clinical Data Coordinator?

AspectFrom Home Clinical Database ProgrammerOn-Site Clinical Data Coordinator
CredentialsTypically requires a degree in health informatics, computer science, or related field; certifications like CDMP or SAS are commonUsually holds a degree in health sciences, nursing, or related field; certifications like CDMP may be preferred
Work EnvironmentRemote, home-based setting with flexible hoursOn-site at clinical trial sites or healthcare facilities
Employer & Industry UsagePharmaceutical companies, CROs, biotech firmsHospitals, clinical research organizations, healthcare providers

While both roles involve managing clinical data, the From Home Clinical Database Programmer works remotely focusing on database development and programming, whereas the On-Site Clinical Data Coordinator handles data collection and management directly at clinical sites. The choice depends on your preference for remote work versus on-site responsibilities.

What are the most commonly searched types of Clinical Database Programmer jobs in Texas?

The most popular types of Clinical Database Programmer jobs in Texas are:

What are popular job titles related to From Home Clinical Database Programmer jobs in Texas?

For From Home Clinical Database Programmer jobs in Texas, the most frequently searched job titles are:

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Cities in Texas with the most From Home Clinical Database Programmer job openings:

AI Database Platform Lead

MethodHub

Dallas, TX • On-site

Other

Posted 21 days ago


Job description

Bisoftllc is looking for AI-First Data Platforms Lead –

Key Responsibilities

•                Own the enterprise database platform strategy, architecture, governance, and technology roadmap.

•                Lead the transformation from traditional DBA operations to an AI-first Database Platform Engineering model.

•                Drive AI-powered automation for database provisioning, monitoring, maintenance, performance tuning, and incident management.

•                Build and manage self-service database provisioning capabilities to accelerate engineering delivery and reduce manual effort.

•                Ensure database platforms are secure, scalable, resilient, highly available, and cost-efficient across on-premises and cloud environments.

•                Lead database modernization, consolidation, migration, and cloud adoption initiatives.

•                Establish standards, best practices, governance, and lifecycle management for enterprise database platforms.

•                Implement observability, predictive monitoring, and AIOps capabilities to proactively prevent outages and improve reliability.

•                Partner with Engineering, Infrastructure, Security, Architecture, and Application teams to deliver platform services and approved patterns.

•                Drive adoption of Infrastructure-as-Code (IaC), DevOps, CI/CD, and Database-as-a-Service (DBaaS) capabilities.

•                Ensure compliance, data protection, access controls, backup, recovery, and disaster recovery readiness.

•                Mentor and develop database engineers while fostering a culture of automation, innovation, and operational excellence.

•                Evaluate emerging database, AI, and cloud technologies to continuously improve platform capabilities.

•                Optimize platform costs through standardization, automation, capacity planning, and resource utilization.

Business Impact

•                Reduces operational risk through intelligent automation and standardized platforms.

•                Improves performance, availability, reliability, and security of enterprise databases.

•                Accelerates provisioning from days to minutes through self-service capabilities.

•                Enhances compliance and governance while reducing manual administrative effort.

•                Lowers long-term support and infrastructure costs through automation and platform rationalization.

•                Enables engineering teams to move faster with AI-enabled platform services and expert guidance.

•                Creates a scalable foundation that supports enterprise growth, cloud strategy, and future AI initiatives.

Key Success Measures

•                Significant reduction in manual DBA effort through AI and automation.

•                Faster database provisioning and deployment cycles.

•                Improved uptime, reliability, and recovery capabilities.

•                Reduced incident volume and Mean Time to Resolution (MTTR).

•                Increased adoption of self-service database services.

•                Lower total cost of ownership (TCO) through optimization and standardization.