Data Engineer

SolutionIT, Inc.

Phoenix, AZ, United States

3 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Compensation

$85,000.0 - $118,000.0

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Microsoft Azure Cloud Computing Cloud Database Cloud Engineering Databases Continuous Integration Data Centers Data Governance Data Security

+30 more

Relational Databases Database Design Database Development Database Security DevOps Disaster Recovery Distributed Data Store Python (Programming Language) PostgreSQL Machine Learning Microsoft SQL Server MongoDB MySQL NoSQL Oracle (Applications) Performance Tuning Query Optimization Azure Machine Learning Search Technologies SQL Databases Data Processing Scripting Google Cloud System Availability Large Language Models Database Performance Generative AI Indexer Database Migration Enterprise Integration

Job description

Design and define enterprise-level database architectures, standards, patterns, and best practices.
Evaluate and select appropriate relational, NoSQL, and cloud-native database technologies based on business and technical requirements.
Design scalable database solutions covering data modeling, availability, resiliency, backup/recovery, replication, and disaster recovery.
Provide expertise in database technologies such as PostgreSQL, MySQL, Oracle, SQL Server, MongoDB, or similar platforms.
Design and support database solutions on cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
Lead or support on-premises-to-cloud database migrations and modernization initiatives.
Optimize database performance through query tuning, indexing, partitioning, capacity planning, and database configuration.
Establish database security standards, including encryption, access controls, auditing, data protection, and compliance requirements.
Collaborate with application architects and engineering teams on database design, APIs, data access patterns, and integration solutions.
Use Python for basic database automation, scripting, data processing, validation, and operational tasks.
Work with AI/ML and GenAI teams to understand data requirements and support AI-enabled applications.
Provide basic architectural guidance for AI-related data patterns, including embeddings, vector databases/vector search, and Retrieval-Augmented Generation (RAG).
Evaluate emerging database, cloud, and AI technologies and recommend solutions where appropriate.
Create and maintain architecture diagrams, database standards, technical documentation, and design decisions.
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Requirements

Strong experience in database architecture, database engineering, or database administration.
Deep understanding of relational database concepts, SQL, data modeling, normalization, indexing, transactions, and performance optimization.
Experience with one or more major database platforms such as PostgreSQL, Oracle, SQL Server, MySQL, MongoDB, or equivalent.
Hands-on experience with AWS, Azure, or GCP, particularly managed database services.
Understanding of cloud architecture concepts including scalability, high availability, security, monitoring, backup, and disaster recovery.
Experience designing or supporting database migration and modernization initiatives.
Basic to intermediate Python skills for scripting, automation, and data processing.
Basic understanding of Artificial Intelligence, Machine Learning, and Generative AI concepts.
Familiarity with AI-related technologies such as vector databases, embeddings, semantic search, LLMs, and RAG is preferred.
Strong problem-solving, analytical, communication, and documentation skills.
Ability to collaborate effectively with architects, developers, data engineers, infrastructure teams, security teams, and business stakeholders.
Experience with cloud-native and distributed database architectures.
Experience with Infrastructure as Code and DevOps/CI/CD practices.
Knowledge of database observability, monitoring, and automated operations.
Experience with data governance, security, privacy, and regulatory requirements.
Exposure to AI/ML platforms and cloud-based AI services.
Experience supporting large-scale, high-volume, highly available enterprise systems