Senior Data Engineer (AI)

TL;DR

Senior Data Engineer (AI): Building and scaling real-time streaming pipelines and batch ETL/ELT processes for a large enterprise contact center solution with an accent on AI-enabled analytics and operational intelligence. Focus on designing low-latency data services, implementing robust LLMOps telemetry, and optimizing data architectures on the Databricks Lakehouse platform.

Location: Must be based in the US and currently authorized to work in the United States without visa sponsorship

Salary: $128,200 – $157,000 + bonus

hirify.global

An enterprise software leader providing unified customer experience platforms for global organizations and government agencies.

What you will do

• Design, build, and operate low-latency streaming pipelines and robust batch ETL/ELT workflows.
• Orchestrate complex data dependencies with high availability and strong SLAs.
• Model and optimize curated datasets for product features, analytics, and AI/RAG workloads.
• Partner with cross-functional teams to ship data products and agentic AI services into production.
• Implement observability, data quality checks, and root-cause analysis to ensure system reliability.
• Manage data security, governance, and compliance controls (SOC 2, GDPR, CCPA).

Requirements

• 6+ years of experience in building production-grade data pipelines at scale.
• Deep proficiency in Python and advanced SQL.
• Strong experience with Spark on Databricks (or similar).
• Hands-on expertise with Kafka and Airflow.
• Must be currently authorized to work in the United States without sponsorship.
• Production mindset including CI/CD, monitoring, alerting, and on-call participation.

Nice to have

• Experience building data services in Go or familiarity with Flink/Beam.
• Experience with cloud migrations (Azure, GCP, or AWS).
• Knowledge of LLMOps telemetry, RAG pipelines, and agentic AI patterns.
• Background in contact center or CRM data systems.

Culture & Benefits

• Competitive compensation package with performance-related bonuses.
• Opportunity to work on large-scale AI-enabled enterprise products.
• Collaborative environment valuing strong connections and mission-driven work.
• Comprehensive employee benefits programs.