Data Support Engineer

We want to contract two Data Support Engineers to own data validation and support-ticket response, keeping the client's reporting and analytics environment accurate, trusted, and running smoothly. These are hands-on, SQL-heavy roles for people who enjoy solving data problems and closing tickets cleanly.

Top two skills:
SQL Query Writing & SQL Data Validation


What You'll Do

• Write and run SQL validation queries against an Amazon Redshift data warehouse to verify data accuracy, completeness, and integrity.

• Execute routine data-quality audits and generate report cards on data health.

• Respond to, triage, and resolve incoming support tickets, escalating complex issues to onshore engineers when needed.

• Investigate data discrepancies between source systems, the warehouse, and downstream reports (e.g., Power BI).

• Document findings, fixes, and repeatable processes in runbooks.

• Monitor pipeline and data-quality alerts and respond per established procedures.

Required Qualifications

• 2+ years in a data support, data analyst, QA, or data engineering role.

• Strong SQL skills — able to write complex queries independently (joins, aggregations, window functions, subqueries).

• Demonstrated experience with data validation and data-quality techniques.

• Hands-on experience with a cloud data warehouse (Amazon Redshift strongly preferred; Snowflake / BigQuery / Azure Synapse acceptable).

• Comfortable working a support-ticket queue and communicating status clearly in English (written and verbal).

• Detail-oriented, organized, and able to work independently across time zones.

Nice to Have

• AWS data stack exposure (Lambda, Step Functions, S3).

• Power BI or other BI/reporting tool familiarity.

• Experience with ticketing systems (Jira, ServiceNow, Zendesk).

• Basic Python or scripting for automation.