Data Pipeline Automation Engineer

Engineering - Data Pipelines & Analytics
Remote · Eastern Time
Contract
$50k – $80k USD

Role Purpose
We are looking for a Data Pipeline Automation Engineer to design and run the data side of our automation practice - one of the core service categories on the REWORK platform. Businesses come to us drowning in manual exports, copy-paste reporting, and data trapped across tools; you will turn those into automated, monitored pipelines that feed dashboards, alerts, and AI workflows. This role is ideal for someone who thinks in flows of data the way an automation specialist thinks in flows of tasks, and who takes pride in pipelines that keep running quietly for months.

Core Responsibilities
Pipeline Design & Integration
Map where business data lives (CRMs, spreadsheets, SaaS tools, databases) and design the pipelines that unify it
Build reliable extract–transform–load flows between platforms, APIs, and warehouses
Automate recurring reports and hand-built spreadsheets out of existence

Analytics & AI-Ready Data
Deliver live dashboards and scheduled reports that replace manual number-pulling
Prepare clean, structured datasets that power AI agents, scoring models, and automations
Reliability & Documentation
Monitor pipeline health, add alerting, and design for graceful failure and recovery
Document data flows and schemas so any teammate can trace a number back to its source

Required Qualifications
Proven track record of building data pipelines or reporting automations businesses actually rely on
1+ years of hands-on experience with SQL and at least one pipeline/ETL toolchain
System Design & Problem-Solving
Strong grasp of data modeling, idempotency, and incremental syncs (source → transform → deliver → monitor)
Detail-oriented; able to debug schema drift, API pagination, and silent data-quality failures
Documentation & Nice-to-Haves
Clear communication with a habit of documenting flows, schemas, and assumptions
Nice to have: dbt or warehouse experience, dashboard design (Looker Studio / Power BI), SaaS / startup / digital-ops background

Key Deliverables
Manual reporting and data-entry hours measurably reduced or eliminatedPipelines running reliably with monitoring and minimal human interventionDashboards and datasets the business actually trusts and usesClear, well-documented data architecture

Tech Stack & Skills
SQL PythonETL / ELTAirbyte / Fivetran n8n Make / IntegromatAPIs & Webhooks Google Sheets / BigQueryLooker StudioPower BIdbtZapier

Expectations
Work asynchronously in a remote-first environment (Slack, email, documented reports)
Operate highly independently - evaluated on proof-of-work and reliability of deliverables
Collaborate during core hours, 10:00 AM – 4:00 PM Eastern Time