CrawlJobs Logo
Augusta Hitech Soft Solutions Logo Augusta Hitech Soft Solutions · IT - Software Development

SQL Ops Engineer

India, Remote · Job Posted February 16, 2026
Apply Position
Job Link Share

Job Description

We are seeking a SQL Ops Engineer to ensure the performance, reliability, security, and availability of SQL database platforms that power healthcare data ecosystems. You will manage operational aspects of relational databases (primarily Microsoft SQL Server), support high-stakes healthcare workloads, and provide foundational stability for data pipelines and applications.

Job Responsibility

  • Install, configure, upgrade, patch, and maintain SQL Server (and other RDBMS) instances in on-prem, cloud, and hybrid environments
  • Perform performance tuning — query optimization, indexing strategies, execution plan analysis, and resource governance
  • Design and implement high availability and disaster recovery solutions (Always On Availability Groups, clustering, replication, backups)
  • Monitor database health, capacity, and performance using native and third-party tools
  • proactively resolve bottlenecks
  • Manage security, encryption, auditing, access controls, and compliance requirements (HIPAA, data privacy, PHI protection)
  • Automate routine operations (maintenance plans, monitoring scripts, alerting) using PowerShell, T-SQL, or Python
  • Troubleshoot and resolve database incidents
  • conduct root-cause analysis and implement permanent fixes
  • Support data migration, integration, and replication projects across systems
  • Collaborate with DataOps Engineers to ensure databases provide optimal support for pipelines and analytics
  • Participate in on-call support and ensure adherence to strict SLAs for uptime and performance in a 24/7 healthcare environment

Requirements

  • 8 years of hands-on experience as a SQL Database Administrator, SQL Ops Engineer, or equivalent
  • Deep expertise in Microsoft SQL Server administration, tuning, and high availability features
  • Strong command of T-SQL, indexing, execution plans, and performance troubleshooting
  • Experience with backup/recovery strategies, security hardening, and compliance in regulated industries
  • Proficiency in automation scripting (PowerShell, T-SQL) and monitoring tools (SQL Server Management Studio, Extended Events, Azure Monitor, or similar)
  • Solid understanding of healthcare data environments and regulatory requirements (HIPAA, PHI)
  • Strong analytical, problem-solving, and documentation skills

Nice to have

  • Experience with Azure SQL Database, Managed Instance, or hybrid cloud SQL setups
  • Knowledge of other RDBMS (PostgreSQL, MySQL) is a plus
  • Exposure to medical device or EMS data platforms
  • Relevant certifications (Microsoft Certified: Azure Database Administrator, MCSE, etc.)
Augusta Hitech Soft Solutions - All Job Offers

Looking for more opportunities?

Search for other job offers that match your skills and interests.

Suggested Tags: Frontend Developer Secretary Talent Manager Salesforce Administrator Data Analyst
Similar Jobs for

SQL Ops Engineer

8 matching positions

Dev Ops Engineer

A DevOps Engineer serves as the engineer of complex technology implementations i...
Location
Location
United States , Los Angeles
Salary
Salary:
Not provided
dashtechinc.com Logo
Dash Technologies
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • automation, CI/CD, security, release governance, Routing, governance, test, deployment, Centralized Logging, Azure AI Search, SSL/TLS, API Management, Release, Strong DevOps engineering expertise across cloud infrastructure, and production operations
  • Hands on experience with Microsoft Azure, including multi subscription architecture, landing zones, and policy enforcement
  • Proficient in designing and managing CI/CD pipelines using GitHub Actions for automated build, rollback, and promotion
  • Skilled in modernizing legacy DevOps processes, including repository migrations and transitioning to standardized pipeline driven delivery
  • Deep knowledge of Infrastructure as Code, configuration driven deployment, and platform standardization using automation and policy controls
  • Experienced in administering and troubleshooting Linux-based and cloud-hosted application environments
  • Proficient with containerization technologies such as Docker and Azure Cont, including image lifecycle management with Azure Container Registry
  • Strong understanding of networking and secure application delivery, including Application Gateway, and firewall policies
  • Advanced knowledge of cloud security, including Managed Identity, zero secret architecture, RBAC, governance policies, and secure access design
  • Skilled in monitoring and observability using Azure Monitor, Log Analytics, diagnostic settings, and alerting
Job Responsibility
Job Responsibility
  • serves as the engineer of complex technology implementations in a product-centric environment
  • comfortable with bridging the gap between legacy development or operations teams and working toward a shared culture and vision
  • works to arm developers with the best tools and ensuring system uptime and performance
  • The DevOps Engineer will deploy and configure services using infrastructure as a service (IaaS) providers (e.g., Amazon Web Services, Microsoft Azure, Google Compute Engine, RackSpace/OpenStack)
  • configure and manage Linux-based servers to serve a dynamic website
  • debug cluster-based computing architectures
  • use scripting or basic programming skills to solve problems
  • install and manage open source monitoring tools
  • use configuration management tools (e.g., Puppet, Chef, Ansible, Salt)
  • Develop architecture for continuous integration and deployment, and continuous monitoring
  • Fulltime
Read More
Arrow Right

ML Ops Engineer

Location
Location
India , Miracle Heights
Salary
Salary:
Not provided
miraclesoft.com Logo
Miracle Software Systems
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Java
  • Python
  • SQL
  • GCP
  • Dockers
  • Terraform
  • Exp 7-10 Years
Job Responsibility
Job Responsibility
  • Design, build, and maintain end-to-end MLOps pipelines for model training, deployment, monitoring, and continuous improvement in production environments
  • Develop backend services and APIs using Python and Java frameworks to operationalize machine learning models
  • Implement automated CI/CD workflows for machine learning and data applications
  • Manage the full model lifecycle, including feature engineering integration, model registry management, version control, and performance tracking
  • Deploy and operate machine learning workloads on Google Cloud Platform using BigQuery, GCS, Dataflow, and Dataproc
  • Deploy applications packaged using Docker and orchestrate deployments with Kubernetes
  • Implement Infrastructure as Code using Terraform for reproducible environment provisioning
  • Establish model observability practices, including drift detection, performance monitoring, and operational reliability controls
  • Collaborate with data scientists, platform engineers, and product teams within Agile delivery environments
  • Maintain SDLC best practices, including source control, security validation, static analysis, and automated quality checks using GitHub, Tekton, SonarQube, 42Crunch, and FOSSA
Read More
Arrow Right

ML Ops Engineer

The MLOps Engineer will work closely with the Data Science, Analytics, and Data ...
Location
Location
United States
Salary
Salary:
127000.00 - 160550.00 USD / Year
zelis.com Logo
Zelis
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • 2–5 years of experience in ML Ops, ML Engineering, or a related role with a focus on production-level model monitoring, automation, and deployment
  • Strong experience with ML observability tools or custom-built monitoring systems
  • Experience with monitoring LLMs and Generative AI models, including prompt evaluation, hallucination tracking, and agent behavior auditing
  • Experience in deploying and managing ML workloads using containerization and orchestration platforms such as Docker, Kubernetes, Kubeflow, or TensorFlow Extended
  • Familiarity with AutoML pipelines and workflow management tools (e.g., MLflow, SageMaker Autopilot)
  • Experience working in cloud environments, preferably AWS (e.g., SageMaker, S3, Lambda, ECS/EKS)
  • Understanding of ML lifecycle tools (e.g., MLflow, SageMaker Pipelines) and CI/CD practices
  • Strong security and compliance awareness, particularly related to model/data governance (e.g., HIPAA, GDPR)
  • Proficiency in Python and key data libraries (Pandas, Numpy, Matplotlib, etc.)
  • Advanced SQL skills and experience with Snowflake or similar data warehousing platforms
Job Responsibility
Job Responsibility
  • Build and maintain monitoring infrastructure for conventional machine learning models, with capabilities for performance tracking, drift detection, and alerting
  • Research, evaluate, and implement monitoring strategies and tools for Generative AI systems, including LLMs and Agentic AI architectures
  • Collaborate with ML Engineers, Data Scientists, and DevOps teams to deploy, manage, and monitor models in production
  • Develop and support scalable, secure, and automated data pipelines using Snowflake, SQL, and Python for training, serving, and monitoring ML and GenAI models
  • Leverage AutoML tools and frameworks (e.g., MLflow, Kubeflow, SageMaker Autopilot) to streamline experimentation and deployment
  • Design dashboards and reporting systems to visualize model health metrics and surface key operational insights
  • Ensure auditability, reproducibility, and compliance for model performance and data flow in production environments, with consideration for regulatory standards like GDPR and HIPAA
  • Maintain CI/CD workflows and version-controlled codebases (e.g., Git) for ML infrastructure and pipelines
  • Utilize containerization and orchestration technologies (e.g., Docker) to manage scalable ML infrastructure
  • Leverage tools such as Streamlit and Python visualization libraries to present insights from model and data monitoring
What we offer
What we offer
  • 401k plan with employer match
  • flexible paid time off
  • holidays
  • parental leaves
  • life and disability insurance
  • health benefits including medical, dental, vision, and prescription drug coverage
  • Fulltime
Read More
Arrow Right

Senior Machine Learning Ops Engineer

As our Senior MLOps Engineer, you will take ownership of our machine learning pl...
Location
Location
Germany , Berlin
Salary
Salary:
Not provided
enpal.com Logo
enpal
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • 4+ years of experience in MLOps, ML engineering, or applied machine learning in production environments
  • Strong ownership mentality—you care about impact, not just implementation
  • Clear communicator who can explain complex ML concepts to non-technical stakeholders
  • Solid experience with cloud infrastructure (Azure preferred), container orchestration (Docker/Kubernetes), and IaC (Terraform)
  • Proven track record with ML lifecycle tooling—model versioning, monitoring, retraining, CI/CD
  • Familiarity with MLFlow, Airflow, or similar platforms
  • Strong programming skills in Python and experience with ML frameworks
  • Hands-on experience with Snowflake, Databricks, or modern data stack tools
Job Responsibility
Job Responsibility
  • Act as AI Act Steward within Enpal - ensure compliance with the EU AI Act and future regulations
  • Build and maintain a central registry of all ML and GenAI use cases and models
  • Design processes to monitor high-risk models, ensuring explainability, robustness, and fairness
  • Design and implement core infrastructure, including: A centralized Model Registry
  • A scalable Feature Store
  • Automated Monitoring systems for both ML and GenAI models
  • Orchestration pipelines for retraining and redeployment (e.g. Airflow-based)
  • Collaborate with Data Engineering to ensure seamless CI/CD for ML workflows
  • Drive implementation of GenAI-based agents that interface with our DWH (e.g. access distribution, text-to-SQL, semantic search, natural language querying)
  • Prototype and deploy agentic LLM workflows using Snowflake and other enterprise data assets
What we offer
What we offer
  • Competitive salary
  • Flexible working arrangements
  • Empowering team culture
  • Hybrid working model
  • Modern office in Berlin-Friedrichshain with amenities (ping-pong table, yoga corner, roof terrace, stocked drinks fridges)
  • Onboarding day to get to know the company, team colleagues and founder
  • Monthly all-hands meetings
  • Lunch & Learn sessions
  • Legendary team spirit and unforgettable team events
  • Strong feedback culture
  • Fulltime
Read More
Arrow Right

Data Ops Engineer

We are looking for a skilled DataOps Engineer to operationalize and industrializ...
Location
Location
India
Salary
Salary:
Not provided
augustahitech.com Logo
Augusta Hitech Soft Solutions
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • 8 years of experience in data engineering or DataOps roles
  • Strong expertise in building and operating data pipelines (ETL/ELT) and orchestration tools
  • Proficiency in Python, SQL, and at least one cloud platform (Azure Synapse, AWS Glue, GCP Dataflow preferred)
  • Hands-on experience with dbt, Airflow, Docker, Kubernetes, and Git
  • Experience with data quality, observability, and testing frameworks
  • Solid understanding of healthcare data concepts, compliance (HIPAA), and regulated environments
  • Excellent problem-solving, collaboration, and communication skills
Job Responsibility
Job Responsibility
  • Design, build, deploy, and optimize end-to-end data pipelines (ingestion, transformation, orchestration, and delivery) using modern DataOps practices
  • Implement CI/CD pipelines for data workflows, including version control, automated testing, and deployment of transformations (e.g., using dbt)
  • Orchestrate complex workflows with tools like Apache Airflow, Prefect, or cloud-native orchestrators
  • Establish monitoring, alerting, and observability for data pipelines — ensuring data freshness, quality, and lineage
  • Perform root-cause analysis on pipeline failures and implement preventive measures
  • Collaborate with data engineers, analysts, data scientists, and business stakeholders to translate requirements into reliable data products
  • Enforce data governance, quality frameworks, and compliance controls (HIPAA, PHI security) in all data processes
  • Automate infrastructure provisioning and support cloud data platforms (Azure, AWS, or GCP)
  • Contribute to continuous improvement of DataOps processes, tools, and standards in the managed services environment
  • Participate in on-call rotation and maintain SLAs for data availability and performance
Read More
Arrow Right

AI Ops Engineer - Finance

You'll make sure no one at Lovable spends time on anything AI can do. We're defi...
Location
Location
Sweden , Stockholm
Salary
Salary:
Not provided
lovable.dev Logo
Lovable
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Shipped production automations at a company: You've built workflow systems at scale that ran without you. Actual business-critical automations used by teams
  • Engineering brain, modern toolkit: You understand how systems actually work (APIs, databases, architecture) and can review code confidently. You move fast by choosing the right tool for the job: AI agents (Cursor, Claude Code etc) when they're faster, no-code (n8n, Lovable itself, Clay, etc.) when it fits, raw code when it's needed. Python, TypeScript, SQL etc
  • AI tool obsessed: You're always testing the latest models, apps, and workflows before anyone else. You've deployed internal AI tools (Claude/ChatGPT with custom contexts, AI agents, MCPs, etc.) at a company and you're constantly experimenting with new ones
  • Can't unsee inefficiency: You see the whole company as one machine. Once you spot a broken process, you can't leave it alone
  • High agency: You don't wait for permission. You find the bottleneck, build the fix, and ship it
Job Responsibility
Job Responsibility
  • Own internal AI systems that make Lovable run faster than it should
  • Define how AI-native companies operate: Help build the playbook. What we learn here scales to every company using Lovable
  • Build internal tools and workflows: Using Lovable, AI agents, no-code, raw code—whatever gets the job done fastest. Lovable on Lovable first, always
  • Deploy AI agent armies: Claude/ChatGPT with MCPs configured so every teammate has AI working for them, not the other way around
  • Squeeze value from our stack: Make the AI features in Slack, Linear, Notion, Ashby, etc. actually deliver
  • Level up the team: Turn everyone at Lovable into AI power users. Document what works. Scale it
  • Own it end-to-end: You build it, you maintain it, you improve it
  • Fulltime
Read More
Arrow Right

Vice President ML Ops Engineer

Embark on a transformative journey as Vice President- ML Operations Engineer at ...
Location
Location
India , Noida
Salary
Salary:
Not provided
barclays.co.uk Logo
Barclays
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Experience in Programming & Automation: Python, Bash, SQL
  • MLOps Tools: MLflow, Kubeflow, AWS SageMaker Pipelines
  • Cloud Platforms: AWS (SageMaker, Bedrock, Lambda, Step Functions, CloudWatch)
  • DevOps Expertise: CI/CD (GitHub Actions, Jenkins), Docker, Kubernetes
  • Data Management: Enterprise data governance, ETL processes
  • Leadership Skills: Strategic planning, team management, stakeholder communication
Job Responsibility
Job Responsibility
  • Definition and oversight of data governance and procedures to address control and regulatory requirements, including Data Privacy
  • Definition and oversight of data analytics and insights that support the effective management of the business and well as driving commercial outcomes
  • Development of a team of data professionals with expertise in data analytics, data engineering, data science, and other relevant disciplines
  • Analysis of the bank's current data landscape, identify key data assets and gaps, and develop a roadmap for future data initiatives
  • Monitoring team performance and setting clear performance expectations
  • Lead the design and governance of MLOps frameworks, AWS-based architectures, and automation strategies to enable efficient, secure, and scalable deployment of AI and Generative AI models
What we offer
What we offer
  • Hybrid working
  • Modern workspaces, collaborative areas, and state-of-the-art meeting rooms
  • Facilities include wellness rooms, on-site cafeterias, fitness centers, and tech-equipped workstations
  • Fulltime
Read More
Arrow Right

Senior Software Engineer, AI & ML Ops

Hyundai AutoEver America seeks a seasoned Senior AI/ML Engineer to architect, de...
Location
Location
United States , Irvine
Salary
Salary:
103170.00 - 158873.00 USD / Year
haeaus.com Logo
Hyundai AutoEver America
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Bachelor’s or Master’s degree in Computer Science, Engineering, AI, or related field
  • advanced degrees/certifications are a plus
  • 8+ years of software engineering experience, including 3+ years in AI/ML solution development
  • Proven experience designing and deploying LLM-based solutions, traditional ML models, RAG systems, and agent workflows
  • Strong expertise in Python, TensorFlow/PyTorch, Hugging Face, prompt engineering, vector databases, and AI orchestration
  • Hands-on experience with AWS SageMaker/Bedrock, Azure OpenAI, or Azure ML Studio, plus MLOps best practices (CI/CD, testing, model monitoring)
  • Proficiency in frontend frameworks (React), cloud-native deployment (Docker/Kubernetes), microservice APIs, and relational/NoSQL databases
Job Responsibility
Job Responsibility
  • Architect and develop scalable AI/ML and LLM-based systems, including RAG pipelines, agentic workflows, predictive models, and generative AI solutions
  • Build full‑stack AI applications, including React-based dashboards and front‑end interfaces integrated with backend services and cloud infrastructure
  • Develop data pipelines and ML Ops workflows using Python, SQL, AWS/Azure platforms, and monitoring tools to train, deploy, and optimize models
  • Lead cross-functional AI initiatives, deliver PoCs/MVPs, ensure compliance with AI governance, and integrate AI features into enterprise and user-facing systems
  • Provide technical leadership and mentorship, guiding standards, code reviews, model documentation, and best practices in AI/ML development
  • Continuously improve AI performance and reliability through prompt engineering, architecture enhancements, and data optimization
What we offer
What we offer
  • comprehensive medical/dental coverage
  • generous PTO
  • education assistance
  • annual merit increase eligibility
  • Fulltime
Read More
Arrow Right