Analytics Engineer, Data Pipelines

We are looking for an experienced Analytics Engineer to own the reporting data pipelines behind the dashboards of a leading media and entertainment company. Working in SQL, Python, Airflow, and Tableau, you will track down why pipelines stall, fix the root cause, retire what no one uses, and build the monitoring that catches the next problem early. Expect a clear backlog, a weekly check-in with the team lead, and no on-call.

After six months, every pipeline you touched will run cleanly, be monitored, and have a formalized runbook.

Schedule: Fully remote, US-only role. Assignment length and any extension or conversion details will be discussed during the hiring process.

Before you apply

• Repair a prioritized backlog of stalled and broken pipelines behind reporting dashboards, fixing each failure at its root cause.
• Replace drop-and-recreate table builds with in-place writes that preserve access permissions.
• Move workflow alerts from deprecated notification settings to a team distribution list, where someone will act on them.
• Inventory Tableau published data sources and embedded SQL, find duplicated logic, and confirm downstream consumers before any change.
• Retire unused workflows and tables in stages: confirm nothing depends on them, disable them for one billing cycle, then remove them.
• Build freshness checks that catch stale dashboard extracts before anyone relies on them.
• As new product types launch, confirm each appears correctly in cost reporting and write a short reconciliation of its first cycle.
• Provide first-line triage when an in-scope workflow fails: about 4 hours a week, business hours only, no on-call.
• Write a runbook for every workflow you touch, and hand all documentation to the client’s team lead.
• Ship every change through pull-request review, and meet weekly with the client’s team lead on progress and priorities.
• By the end of the engagement, leave every pipeline you touch running cleanly, monitored, and documented.

• 3+ years in analytics or data engineering, including hands-on ownership of production pipelines.
• Strong SQL on a distributed query engine such as Trino or Presto.
• Python and pandas for data processing and validation.
• Experience building and maintaining scheduled workflows in an orchestration tool such as Airflow.
• Working knowledge of Tableau published data sources and extracts.
• Fluency in git and pull-request review.
• A record of debugging sparsely documented pipelines you did not build, down to the root cause.
• The habit of confirming who depends on something before you change or remove it.
• The independence to work from a prioritized backlog between weekly check-ins.
• Clear writing: runbooks and summaries a teammate can follow without you.
• Must be able to use a Mac as the primary working device for this assignment.
• Must be located in the United States and perform work from within the United States.
• Must be eligible to work directly for Blue In Green  in a W2 hourly with benefits role.
• Direct applicants only; no recruiting agencies, third-party vendors, employer-of-record arrangements, or corp-to-corp submissions.
• Must be legally authorized to work in the United States and able to complete Form I-9 employment eligibility verification if hired.
• Must be willing to complete a background check, subject to applicable law and required candidate authorization.
• Must understand that this is an hourly W2 role with benefits eligibility and that assignment length or extension is not guaranteed.

• Billing, cost, or financial reporting data.
• Data-quality monitoring: freshness checks, alerting, or similar.
• Retiring legacy workflows or tables without breaking what depends on them.
• Iceberg or Hive table formats.
• Jupyter notebooks and parameterized runs with a tool such as papermill.
• Airtable, for read-only reporting.
• Media, localization, or content supply chain data.

You will answer a few practical questions in the application so we know the role details line up.

The questions are included in the application form.