W2 Data Engineer

Overview
Inabia is seeking an experienced Data Engineer with strong expertise across data engineering, database architecture, cloud platforms, and application architecture. This role is responsible for designing and implementing reliable, scalable, secure, and high-performance data solutions in close collaboration with application architects, cloud engineers, data scientists, and application development teams. The ideal candidate brings hands-on experience building scalable data pipelines and platforms, deep SQL and data modeling skills, working Python knowledge, and meaningful exposure to AI/ML and Generative AI technologies.

Responsibilities

Design and define enterprise-level database architectures, standards, patterns, and best practices
Evaluate and select relational, NoSQL, and cloud-native database technologies based on business and technical requirements
Design scalable database solutions encompassing data modeling, availability, resiliency, backup/recovery, replication, and disaster recovery
Provide platform expertise across PostgreSQL, MySQL, Oracle, SQL Server, MongoDB, or similar systems
Design and support database solutions deployed on AWS, Azure, or GCP
Lead or support on-premises-to-cloud database migrations and modernization initiatives
Optimize database performance through query tuning, indexing, partitioning, and capacity planning
Establish and enforce database security standards including encryption, access controls, auditing, data protection, and regulatory compliance
Use Python for database automation, scripting, data processing, validation, and operational tasks
Collaborate with AI/ML and GenAI teams, providing architectural guidance on embeddings, vector databases/search, and RAG patterns
Create and maintain architecture diagrams, database standards documentation, and technical reference materials
Provide technical leadership, conduct architecture reviews, support troubleshooting efforts, and mentor team members
Key Qualifications
Strong experience in database architecture, engineering, or administration at enterprise scale
Deep understanding of relational database concepts: SQL, data modeling, normalization, indexing, transactions, and performance optimization
Hands-on experience with one or more major database platforms (PostgreSQL, Oracle, SQL Server, MySQL, MongoDB, or equivalent)
Hands-on experience with AWS, Azure, or GCP managed database services
Solid understanding of cloud architecture principles: scalability, high availability, security, monitoring, backup, and disaster recovery
Demonstrated experience with database migration and modernization projects
Basic to intermediate Python skills for scripting, automation, and data processing
Experience with cloud-native and distributed database architectures, Infrastructure as Code (IaC), and DevOps/CI/CD practices
Knowledge of database observability, monitoring, and automated operations
Experience with data governance, security, privacy, and regulatory compliance requirements
Proven track record supporting large-scale, high-volume, highly available enterprise systems
Strong problem-solving, analytical, written communication, and documentation skills

Preferred Qualifications

Familiarity with vector databases, embeddings, semantic search, large language models (LLMs), and Retrieval-Augmented Generation (RAG) patterns
Basic understanding of AI/ML and Generative AI concepts as they relate to data platform design