Data Operations Engineer DataOps Specialist (AI + LLM)
Job Location:
Philadelphia, PA - USA
Monthly Salary:
Not Disclosed
Posted on:
1 hour ago
Vacancies:
1 Vacancy
Job Summary
Role: Data Operations Engineer / DataOps Specialist
Skills: Digital : Python
Experience Required: 10 years
Primary Skill: LangChain LangGraph VectorDB Python LLMs
Secondary skill: Pl-SQL with ETL tools
Big Data tools (Spark Hadoop)
Cloud Platforms (AWS / Azure / GCP)
Data Modeling & Data Architecture
APIs & Data Integration
CI/CD & Automation tools
DataOps Core Skills
Pipeline orchestration & automation
Data quality frameworks
Monitoring & observability (logs alerts)
Data governance & lineage
Batch & real-time processing
Analytics & BI
Tableau / Power BI
Data visualization & reporting
KPI and dashboard development
Role Descriptions:
1. Data Pipeline & Operations
Build manage and monitor ETL/ELT pipelines for data ingestion and transformation Ensure smooth data flow across systems warehouses and applications
Automate workflows and reduce manual data handling
2. Data Quality & Governance
Implement data validation cleansing and reconciliation processes
Maintain data integrity consistency and accuracy across systems.
Define and enforce data governance standards and policies
3. Monitoring & Issue Resolution
Monitor pipelines and data systems for failures and anomalies
Perform root cause analysis and corrective actions
Ensure SLA adherence for data availability
4. Infrastructure & Performance Optimization
Manage data platforms (AWS/Azure/GCP Data Lakes Warehouses)
Optimize performance scalability and cost efficiency
Support CI/CD for data systems (DataOps practices)
Skills: Digital : Python
Experience Required: 10 years
Primary Skill: LangChain LangGraph VectorDB Python LLMs
Secondary skill: Pl-SQL with ETL tools
Big Data tools (Spark Hadoop)
Cloud Platforms (AWS / Azure / GCP)
Data Modeling & Data Architecture
APIs & Data Integration
CI/CD & Automation tools
DataOps Core Skills
Pipeline orchestration & automation
Data quality frameworks
Monitoring & observability (logs alerts)
Data governance & lineage
Batch & real-time processing
Analytics & BI
Tableau / Power BI
Data visualization & reporting
KPI and dashboard development
Role Descriptions:
1. Data Pipeline & Operations
Build manage and monitor ETL/ELT pipelines for data ingestion and transformation Ensure smooth data flow across systems warehouses and applications
Automate workflows and reduce manual data handling
2. Data Quality & Governance
Implement data validation cleansing and reconciliation processes
Maintain data integrity consistency and accuracy across systems.
Define and enforce data governance standards and policies
3. Monitoring & Issue Resolution
Monitor pipelines and data systems for failures and anomalies
Perform root cause analysis and corrective actions
Ensure SLA adherence for data availability
4. Infrastructure & Performance Optimization
Manage data platforms (AWS/Azure/GCP Data Lakes Warehouses)
Optimize performance scalability and cost efficiency
Support CI/CD for data systems (DataOps practices)