Support Engineer — SEG (Support Engineering Group), AdTech Reporting

Team: Support Engineering Group (SEG)

Focus: Reporting-discrepancy diagnostics, data-pipeline support, and support automation for the AdTech campaign-reporting platform

About the Role

You sit at the boundary between customer support and data engineering. When advertisers or internal reps report that campaign metrics look wrong — impressions over 100%, missing completions, zero views, doubled rows — you own the investigation end to end:

reproduce, query the data, find the root cause across the ingestion pipeline, and either fix the reported data or route it to the right engineering team. You'll also extend the SEG diagnostic tooling (e.g. seg-diagnostic-bot) so recurring issues get triaged automatically instead of by hand.

What You'll Do

- Investigate reporting discrepancies raised as Jira (WPS) tickets: reproduce the issue, trace it through the data pipeline, and confirm root cause with evidence (SQL results, logs, pipeline run history) — never assumptions.
- Write and run read-only SQL diagnostics against AWS Aurora MySQL (and other data stores) to isolate bad, missing, or duplicated rows.
- Trace multi-stage data pipelines (L1 → L2 → L4 → Aurora) built on Apache Spark and orchestrated with Airflow, identifying failed joins, timing races, and destructive-delete/re-insert bugs.
- Work across GCP (BigQuery, Dataform)



and AWS data services to follow data lineage from raw events to customer-facing reports.
- Debug the platform — a PHP (CodeIgniter/CI4) application — to understand how metrics are computed and surfaced in customer dashboards.
- Document findings rigorously: post Jira comments that always include the exact SQL and its actual output, so any engineer can verify the conclusion.
- Propose fixes and coordinate execution with data/platform engineering — and never run state-changing DML in any workplace without explicit approval.

Required Qualifications

- 3+ years in technical support engineering, data support, analytics engineering, or a similar data-heavy role.
- Strong SQL — comfortable writing non-trivial diagnostic queries, joins, and aggregations, and reasoning about schemas (DESCRIBE /

SHOW CREATE TABLE before concluding).

- Hands-on experience with AWS (RDS/Aurora MySQL at minimum) and familiarity with GCP (BigQuery a plus).
- Working knowledge of Apache Spark and Airflow — able to read DAGs, inspect job/task runs, and understand batch data flow.
- Ability to read and debug PHP application code.
- Strong Jira/ticketing discipline and clear written communication.

Nice to Have

- AdTech / campaign-reporting domain knowledge (impressions, completions, CTV/OTT, TTD, DBM/TrueView).
- Experience building support-automation bots or self-service diagnostics.
- Docker, Git, and CI/CD familiarity.

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