Data Operations Engineer / DataOps Specialist (AI + LLM)
Posted Updated
Description
Role: Data Operations Engineer / DataOps Specialist
Skills: Digital : Python
Experience Required: 10+ years
Primary Skill: LangChain, LangGraph, VectorDB, Python, LLM's
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, LLM's
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)