Role: Technical Lead – Data Engineering

Location: Hybrid – Tempe, Arizona.

FULLTIME


Role Overview

We are seeking an experienced Onsite Technical Lead to serve as the primary bridge between the client and an offshore delivery team across various active workstreams that includes Production Support Operations, Application Development & Maintenance. The ideal candidate combines strong hands-on data engineering skills with the communication, coordination, and business acumen needed to operate effectively in a fast-paced client environment. While there would be multiple workstreams in scope, production support takes priority — the ability to respond quickly, communicate clearly under pressure, and ensure SLA adherence is essential.


Key Responsibilities

  • Serve as the onsite point of contact for the client, coordinating day-to-day activities across support and development.
  • Lead morning production support operations — pipeline monitoring, incident triage, data validation, and escalation — ensuring data readiness SLAs are met
  • Act as the primary communication bridge between client stakeholders and the offshore ITCI delivery team — translating business needs into technical direction and vice versa
  • Design and develop scalable Snowflake-based data solutions and ELT/ETL pipelines as part of ADM delivery
  • Develop and manage Airflow workflows and orchestration frameworks
  • Implement Spec-Driven Development using Cursor and AI-assisted engineering practices.
  • Create Power BI-ready semantic layers and analytics datasets; support executive reporting validation
  • Drive automation, testing, monitoring, and CI/CD best practices across all three tracks
  • Coordinate stand-ups, status updates, and stakeholder communications — ensuring offshore team context is current and client expectations are managed proactively
  • Demonstrate flexibility and ownership during critical business periods, including early-morning support windows and time-sensitive incidents



Experience Required & Education

  • 8–12 years of experience in Data Engineering, Cloud Data Platforms, or a combination of engineering and technical delivery roles
  • Bachelor’s or master’s degree in computer science, Engineering, or a related field


Must-Have

  • Strong expertise in Snowflake (Architecture, Data Modelling, Performance Tuning, Streams & Tasks)
  • Strong expertise in Python and advanced SQL
  • Experience building and supporting scalable ETL/ELT pipelines in production environments
  • Strong knowledge of Apache Airflow for workflow orchestration and DAG-level incident management
  • Hands-on experience with AWS services — S3, Glue, Lambda, CloudWatch, Secrets Manager, SNS/SQS
  • Experience with Power BI datasets, semantic models, and report validation
  • Strong understanding of Git, CI/CD, and DataOps practices
  • Proven experience in a client-facing or embedded onsite role — managing stakeholder expectations, communicating technical status clearly, and maintaining trust during incidents.
  • Demonstrated ability to coordinate between an onsite client environment and an offshore or distributed delivery team
  • Hands-on production support experience with defined SLAs — owning incident response from detection through resolution and RCA
  • Ability to triage, prioritize, and route incoming requests across parallel workstreams without creating delivery bottlenecks
  • Experience integrating data from APIs, SaaS applications, and enterprise systems


Good to Have

  • Hands-on experience with Snowflake Cortex (Cortex Analyst, Cortex Search, AI-powered analytics)
  • Proficiency in Cursor IDE and AI-assisted or Spec-Driven Development (SDD)
  • Experience with Terraform and Infrastructure as Code
  • Exposure to Datadog or enterprise monitoring tools
  • Experience with AI/GenAI-driven data engineering solutions
  • Familiarity with running parallel workstreams — balancing operational support priorities against active development delivery
  • Experience with structured change management processes (CAB, change tickets, deployment approvals) in an enterprise client environment
  • Retail, Consumer, or QSR domain experience
  • Experience working in Agile product delivery teams
  • Exposure to modern data platform modernization initiatives


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