Support Manager

TEGNA Inc. • New York, NY

2d • Onsite

About The Position

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.

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.

Nice To Haves

• 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.

Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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.

Benefits

• Two medical plan options for full and part-time employees through Blue Cross Blue Shield of Texas
• Access to dental and eye care coverage
• Fertility, surrogacy and adoption assistance
• Disability and life insurance
• 401(k) program with company match
• Nine free virtual doctor’s appointments with a physician through Teladoc
• 12 free annual therapy sessions with a licensed clinician through Spring Health
• Generous Paid Time Off (PTO)
• Nine paid holidays per year

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level