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# Senior Data Engineer

- **Company:** Pyramid Consulting Inc.
- **Location:** Chandler, AZ, United States
- **Experience:** Expert
- **Salary:** $141,440.0
- **Contract:** Contract
- **Skills:** Training Data, Artificial Intelligence, Data Analysis, Software Documentation, Data Architecture, Data Validation, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Profiling, Digital Assets, Python (Programming Language), Meta-Data Management, Network Configuration and Change Management, Search Technologies, SQL Databases, Unstructured Data, Enterprise Data Management, Enterprise Software Applications, Computer Network Operations, Data Classification, Retrieval-Augmented Generation, Apache Spark, Storage Technologies, Data Lineage, Data Pipelines
- **Published:** October 31, 2026
- **Apply:** https://www.dice.com/job-detail/3012f70e-659b-4415-9ae2-3d9243f32228

## About the Role

* Key Skills: Spark, Python, Data Modelling, Data Quality
 * Financial services
 * 5+ Years of Spark
 * 5+ years of total Data Engineer experience
 * 3+ years of Data Modelling experience

## Description

Immediate need for a talented Senior Data Engineer. This is a 18+ months contract opportunity with long-term potential and is located in Chandler, AZ (Hybrid). Please review the job description below and contact me ASAP if you are interested., * Data Engineering & Pipeline Development: Design, develop, and maintain scalable data pipelines to ingest, process, transform, and integrate structured and unstructured data from multiple enterprise sources using Python, SQL, ETL/ELT frameworks, and data integration technologies.

 * Build reliable data processing workflows to support AI, analytics, automation, and enterprise applications.
 * Data Architecture & AI-Ready Data Preparation: Develop and maintain data models, storage architectures, and data transformation frameworks to organize and prepare enterprise data for AI/GenAI consumption.
 * Work with operational documentation, network configurations, technical standards, policies, logs, telemetry, and runbooks to create structured, searchable, and reusable knowledge assets.
 * Support RAG, embeddings, vector databases, semantic search, and context retrieval use cases.
 * Data Governance & Metadata Management: Implement data governance standards and frameworks covering data quality, metadata management, data lineage, data ownership, stewardship, data classification, retention, and lifecycle management.
 * Establish standards for data definitions, documentation, traceability, and accessibility to ensure enterprise data is accurate, consistent, secure, and suitable for downstream AI applications.
 * Data Quality, Validation & Monitoring: Develop automated data quality checks, validation rules, data profiling, monitoring frameworks, and preventative/detective controls to ensure data accuracy, completeness, consistency, and freshness.
 * Identify upstream data issues, perform root cause analysis, implement remediation strategies, and continuously optimize data pipelines and transformation processes.
 * Cross-Functional Collaboration & Continuous Improvement: Collaborate with engineering, architecture, product, network operations, and governance teams to understand business and technical requirements and translate operational knowledge into reliable data assets.
 * Establish reusable data engineering patterns, documentation standards, and best practices while monitoring data health, pipeline performance, governance compliance, and overall readiness of data for AI-driven solutions.