Act as the primary escalation point for production data issues across Snowflake, dbt, and Airflow environments.
Monitor and troubleshoot Airflow DAG failures, task retries, SLA misses, and dependency issues.
Investigate dbt model failures, test failures, and freshness alerts; coordinate fixes with data engineering teams.
Diagnose Snowflake performance issues, query failures, access problems, and data discrepancies.
Data Quality & Reliability
Define and enforce data quality standards using dbt tests, freshness checks, and custom validation logic.
Perform root cause analysis for recurring data incidents and implement preventative controls.
Partner with engineering teams to improve pipeline observability, alerting, and error handling.
Incident Management & Stakeholder Communication
Manage data incidents from detection through resolution, ensuring timely communication to business stakeholders.
Provide clear status updates, impact assessments, and post-incident summaries to leadership and partners.
Establish and maintain operational runbooks and support documentation.
Operational Excellence & Process Improvement
Define SLAs and support workflows for data pipelines and analytics deliverables.
Drive automation and self-service improvements to reduce recurring support tickets.
Collaborate with platform teams on deployment, access management, and environment promotions.
Team Leadership & Mentorship
Mentor and guide data support analysts and junior engineers on Snowflake, dbt, and Airflow best practices.
Review SQL queries, dbt models, and operational procedures for quality and consistency.
Support onboarding and training of new team members.
Requirements
Bachelor's degree in computer science, Information Systems, Data Analytics, or a related field.
5+ years of experience in data operations, data engineering support, or analytics engineering roles.
Strong hands-on experience with Snowflake, including query optimization, warehouse management, and access control.
Experience supporting and debugging dbt models, tests, sources, and deployments.
Solid understanding of Apache Airflow concepts including DAG design, scheduling, retries, and monitoring.
Advanced SQL skills and strong analytical problem-solving ability.
Excellent written and verbal communication skills, with experience interacting with technical and non-technical stakeholders.
Experience with cloud platforms such as AWS or GCP.
Experience with CI/CD pipelines for analytics engineering (dbt Cloud or GitHub Actions).
Knowledge of data governance, lineage, and metadata management.
Basic scripting experience (Python, Bash) for automation and operational tooling.
Key Competencies
Strong ownership mentality and ability to manage incidents end-to-end.
Detail-oriented with a focus on data accuracy and reliability.
Ability to balance operational support with longer-term platform improvements.
Collaborative mindset with a service-oriented approach.
Comfortable working in fast-paced, production environments.
Work Environment
Onsite based in New York, NY.
May include occasional on-call or after-hours support responsibilities for critical data pipelines.
Benefits
Our 401(k) program offers full, part-time and temporary employees the opportunity to contribute 1% - 80% of their pay on a pre-tax basis to TEGNA's 401(k). Contributions made up to the first 4% of pay are eligible for a 100% match from the company and are 100% vested from day one.Regardless of participation in TEGNA medical plans, ALL employees and their eligible family members receHealth insuranceDental insuranceVision insurance401(k)
Additional Information
About TEGNA
TEGNA Inc. (NYSE: TGNA) helps people thrive in their local communities by providing the trusted local news and services that matter most. With 64 television stations in 51 U.S. markets, TEGNA reaches more than 100 million people monthly across the web, mobile apps, streaming, and linear television. Together, we are building a sustainable future for local news.
Support Manager is responsible for ensuring the reliability, accuracy, and operational excellence of the organization's modern data platform built on Snowflake, dbt, and Airflow. This role serves as the primary escalation point for data incidents, oversees day-to-day data support operations, and partners closely with Data Engineering, Analytics, and Platform teams to maintain high-quality, business-critical datasets. The Data Support Lead also leads process improvements, establishes data support standards, and mentors junior team members.
Tegnainc · New York, NY