april
Engineering
Full-CycleDataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Full-Cycle Data Engineer at april. Skills: Data pipelines, Data modeling, Dashboards, Reporting, SQL, Python. Design, build, and deploy scalable data pipelines from product and system sources in production. Work with distributed query engines such as BigQuery or Athena, with SQL throughout”
What You'll Achieve.
Own the flow from product data sources → modeling → dashboards → insights; Turn raw product data into reliable analytics infrastructure that drives decisions across the company; Take data products from ideation through engineering, analytics, and production deployment; Answer their own questions; Influence the product roadmap and feature prioritization
Industry & Context.
Ability to turn business questions into data models, metrics, and dashboards
What They're Looking For.
Must Have
5+ years in data engineering, data analytics, or product analytics, SQL and hands-on experience with large-scale datasets in cloud data warehouses (BigQuery or similar), Production Python experience for data pipelines, Solid grounding in product metrics, funnels, and user behavior analysis, Ability to turn business questions into data models, metrics, and dashboards
Nice to Have
Streaming or event-driven data systems, Product instrumentation and tracking design, AI/ML or LLM experience, High-scale SaaS or consumer product environments
What You'll Do.
and deploy scalable data pipelines from product and system sources in production
Work with distributed query engines such as BigQuery or Athena
Build and maintain semantic data models for large-scale operational systems and data lakes
Improve the end-to-end analytics stack
from ingestion to visualization
and reliability across the stack
Build and maintain dashboards and reporting layers in tools like Looker or Metabase
Create self-serve analytics
Support product experimentation
Translate ambiguous questions from product leads
and others into clear metrics
and analytical models
Surface trends in usage and user behavior that influence the product roadmap and feature prioritization
Provide ad-hoc analysis and strategic reporting for leadership
How You'll Work.
Team & Collaboration
Partner with product managers, engineers, and AI teams; Collaborate with engineering on event tracking and instrumentation; cross-functional collaboration skills
Communication Scope
communication; communication and cross-functional collaboration skills
Full Job Description
ABOUT THE ROLE We're looking for a Full-Cycle Data Engineer to join our Data & AI team and own the flow from product data sources → modeling → dashboards → insights. You'll partner with product managers, engineers, and AI teams to turn raw product data into reliable analytics infrastructure that drives decisions across the company — from individual feature bets to CEO- and CFO-level questions. This is an end-to-end role: you'll take data products from ideation through engineering, analytics, and production deployment. RESPONSIBILITIES PIPELINES & INFRASTRUCTURE - Design, build, and deploy scalable data pipelines from product and system sources in production, using Python and orchestrators like Airflow. - Work with distributed query engines such as BigQuery or Athena, with strong SQL throughout. - Build and maintain semantic data models for large-scale operational systems and data lakes, manually or with tooling like dbt. - Improve the end-to-end analytics stack, from ingestion to visualization, and collaborate with engineering on event tracking and instrumentation. - Ensure data quality, consistency, and reliability across the stack. ANALYTICS & REPORTING - Build and maintain dashboards and reporting layers in tools like Looker or Metabase, optimized for performance, usability, and clarity. - Create self-serve analytics so product and business stakeholders can answer their own questions. - Support product experimentation: A/B testing, funnel analysis, feature adoption. Partnership & insight - Translate ambiguous questions from product leads, the CEO, the CFO, and others into clear metrics, KPIs, and analytical models. - Surface trends in usage and user behavior that influence the product roadmap and feature prioritization. - Provide ad-hoc analysis and strategic reporting for leadership. REQUIREMENTS - 5+ years in data engineering, data analytics, or product analytics. - Strong SQL and hands-on experience with large-scale datasets in cloud data warehouses (BigQuery
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