Data Sustain Lead – Customer Marketing Platform

ZipStaff•Charlotte, NC

3d•Onsite

About The Position

ZipStaff is seeking a Data Sustain Lead for BAU and L2/L3 support of a Customer Marketing data platform at a global technology services firm. You will own pipeline health, incident triage, ETL troubleshooting, and knowledge management against an automated sustain model. This is a production data-sustain seat with a rotational 24x7 shift — not a greenfield data-engineering build role.

Requirements

5+ years in data platform, application, or ETL sustain / production support.
BAU monitoring of pipelines, batch jobs, and SLAs.
ServiceNow incident and change management (P1–P4).
Hands-on ETL troubleshooting: SAP BODS, Informatica IICS, Airflow, or Snowflake tasks and streams.
SQL root-cause analysis and source-to-target reconciliation, including MS SQL Server.
Runbooks, SOPs, and knowledge management (Confluence / KEDB).
Scripting for automation (Python, Shell, or PowerShell).
Grafana, GitHub Copilot, and practical prompt engineering on support work.
Willingness to work rotational 24x7 shifts with US EST overlap and on-call.
Ability to work on-site in Charlotte, NC.
Must be legally authorized to work in the United States without sponsorship now or in the future.

Nice To Haves

Prior application, data, or platform sustain program.
Snowflake administration, Airflow DAG debugging, dbt tests.
AWS fundamentals (Lambda, S3, CloudWatch, IAM).
Data-quality frameworks (Great Expectations, Soda, or custom SQL DQ).
Chaos or resilience testing.
Banking or customer-marketing data.

Responsibilities

Monitor data pipelines and marts: health checks, batch jobs, and SLA tracking.
Triage and resolve incidents in ServiceNow (P1–P4) to response and resolution SLAs.
Troubleshoot ETL and data pipelines (SAP BODS, Informatica IICS, Airflow, Snowflake tasks and streams).
Run SQL root-cause analysis and reconcile source to target.
Execute and improve runbooks, SOPs, and KEDB articles.
Support automated monitoring (AWS Lambda, SP mailer, CloudWatch, custom data-quality checks) and Grafana dashboards.
Manage changes in ServiceNow: implementation verification and rollback.
Author problem-management RCAs and track permanent fixes.
Maintain Confluence pages, KEDB entries, and runbooks.
Script automation and self-healing in Python, Shell, or PowerShell.
Use GitHub Copilot and prompt engineering where they speed sustain work, without replacing tested runbooks.
Work a rotational 24x7 shift with US EST overlap and on-call, and communicate clearly with onshore stakeholders during incidents.