Senior Data Engineer

Avaya is an enterprise software leader that helps organizations and government agencies connect effectively. The Senior Data Engineer will design and operate low-latency streaming pipelines and robust batch ETL/ELT processes, ensuring data quality and compliance while collaborating with application teams and analytics to deliver data products.

Responsibilities:

• Design, build, and operate low-latency streaming pipelines (Kafka, Spark Structured Streaming) and robust batch ETL/ELT on Databricks Lakehouse
• Establish reliable orchestration and dependency management (Airflow), with strong SLAs and on-call readiness for business-critical data flows
• Model, optimize, and document curated datasets and interfaces that serve analytics, product features, and AI workloads
• Implement data quality checks, observability, and backfills; drive root-cause analysis and incident prevention
• Partner with application teams (Go/Java), analytics, and ML/AI to ship data products into production
• Build and maintain datasets and services that power RAG pipelines and agentic AI workflows (tool-use/function calling)
• When Spark/Databricks isn’t optimal, design and operate custom processors/services in Go to meet strict latency or specialized transformation requirements
• Instrument prompt/response and token usage telemetry to support LLMOps evaluation and cost optimization; provide datasets for labeling and golden sets
• Improve performance and cost (storage/compute), review code, and raise engineering standards
• Design data solutions aligned to enterprise security, privacy, and compliance requirements (e.g., SOC 2, ISO 27001, GDPR/CCPA as applicable), partnering with Security/Legal
• Implement RBAC/ABAC and least-privilege access; manage service principals, secrets, and key rotation; enforce encryption in transit and at rest
• Govern sensitive data: classification, PII handling, masking/tokenization, retention/archival, lineage, and audit logging across pipelines and storage
• Build observability for data security and quality; support incident response, access reviews, and audit readiness
• Embed controls in CI/CD (policy checks, dependency vulnerability scanning) and ensure infra-as-code adheres to guardrails
• Partner with security engineering on penetration tests, threat modeling, and red-team exercises; remediate findings and document controls
• Contribute to compliance audits (e.g., SOC 2/ISO 27001) with evidence collection and continuous control monitoring; support DPIAs/PIAs where required

Requirements:

• 6+ years building production-grade data pipelines at scale (streaming and batch)
• Deep proficiency in Python and SQL; strong Spark experience on Databricks (or similar)
• Advanced SQL: window functions, CTEs, partitioning/z-ordering, query planning and tuning in lakehouse environments
• Hands-on with Kafka (or equivalent) and an orchestrator (Airflow preferred)
• Strong data modeling skills and performance tuning for low latency and high throughput
• Production mindset: SLAs, monitoring, alerting, CI/CD, and on-call participation
• Proficient using AI coding assistants (Cursor, Claude Code) as part of daily development
• Proficiency building data services/processors in Go (or willingness to ramp quickly), and familiarity with alternative frameworks (e.g., Flink/Beam) is a plus
• Experience in multi-cloud or cloud migration (Azure plus either GCP or AWS)
• Exposure to building data for AI/RAG, LLM-powered features, and agentic AI patterns (tool-use/function calling, planning/execution, memory)
• Familiarity with LLMOps telemetry (prompt/response logs, token budgets) and agent evaluation pipelines
• Background in high-scale product engineering (vs. internal IT-only projects)
• Contact center or CRM data familiarity (nice-to-have, not required)
• Bachelor's or Master's in CS/EE/Math or similar; strong academic background and/or top-tier companies