Data Engineer

Job Title: Senior Data Engineer – Snowflake & AI Data Platform

Fulltime Permanent RoleKey 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-HaveStrong expertise in Snowflake (Architecture, Data Modelling, Performance Tuning, Streams & Tasks) Strong expertise in Python and advanced SQLExperience 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/SQSExperience 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 RCAAbility 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 HaveHands-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