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# Data Operations Engineer / DataOps Specialist

- **Company:** Artech
- **Location:** Philadelphia, PA, United States
- **Experience:** Expert
- **Salary:** $93,600.0 - $104,000.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Agile Methodology, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Databases, Data Architecture, Data Validation, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), DevOps, Apache Hadoop, Python (Programming Language), Meta-Data Management, Operational Databases, Systems Development Life Cycle, DataOps, Enterprise Data Management, Pinecone, Scripting, Enterprise Software Applications, Data Ingestion, LangChain, Large Language Models, Prompt Engineering, Apache Spark, Generative AI, Git, Kubernetes, Data Lineage, Weaviate, Milvus, Data Management, FAISS, Restful APIs, Terraform, Stream Processing, Data Pipelines, Automation Anywhere, Docker, Jenkins, ChromaDB
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/data-operations-engineer-dataops-specialist-philadelphia-pa--823cac1b-f57a-4b43-8aff-30a470249da3

## About the Role

Database Extract Transform and Load (ETL), Artificial Intelligence (AI), Python Programming/Scripting Language, Data Management, Best Practices, Cloud Computing, Data Quality, Scalable System Development, Production Systems, Production Control, * 10+ years of experience in Data Engineering, Data Operations, or DataOps.

 * Strong experience building enterprise-scale ETL/ELT pipelines.
 * Hands-on experience with Python-based data engineering and automation.
 * Experience working in Agile and DevOps environments., * Python
 * LangChain
 * LangGraph
 * Large Language Models (LLMs)
 * Vector Databases (Pinecone, Milvus, Weaviate, ChromaDB, FAISS)
 * Prompt Engineering
 * AI Data Pipelines

## Description

We are seeking an experienced Senior Data Operations Engineer (DataOps Specialist) with 10+ years of experience in designing, building, and managing modern data platforms and AI-enabled data pipelines. The ideal candidate will have strong expertise in Python, LangChain, LangGraph, Vector Databases, LLM applications, ETL/ELT frameworks, cloud platforms, and DataOps best practices.

This role is responsible for building scalable data pipelines, ensuring data quality, automating workflows, monitoring production systems, and supporting AI/GenAI data platforms across enterprise environments., * ETL Tools

 * Apache Spark
 * Hadoop Ecosystem
 * AWS / Azure / GCP
 * Data Modeling
 * Data Architecture
 * REST APIs
 * Data Integration
 * Git
 * CI/CD Pipelines
 * Docker
 * Kubernetes
 * Jenkins
 * Terraform (preferred), Data Pipeline Development

 * Design, develop, and maintain scalable ETL/ELT data pipelines.
 * Build automated workflows for data ingestion, transformation, and processing.
 * Support both batch and real-time data processing frameworks.
 * Develop reusable Python components for enterprise data operations.
 * Integrate structured and unstructured data sources., * Build Retrieval-Augmented Generation (RAG) pipelines using LangChain and LangGraph.
 * Develop AI workflows utilizing Vector Databases.
 * Integrate enterprise applications with Large Language Models.
 * Optimize prompt engineering strategies and LLM orchestration.
 * Manage embeddings, document indexing, and semantic search pipelines., * Implement automated data validation and reconciliation processes.
 * Develop data quality monitoring frameworks.
 * Ensure consistency, integrity, and reliability of enterprise datasets.
 * Support metadata management and data lineage.
 * Enforce enterprise data governance standards., * Monitor production data pipelines and workflows.
 * Detect and resolve pipeline failures.
 * Perform root cause analysis for data issues.
 * Implement alerting and observability solutions.
 * Ensure SLA compliance and operational stability.