Sr. Data Engineer

Entyre Inc

Boston, Massachusetts, United States

Boston, Massachusetts, United States

Postuler Maintenant

À propos

Overview We are hiring a Senior Data Engineer to own and evolve our analytics data platform. The infrastructure is already in place (PostgreSQL, Airflow, Jupyter, SQLMesh). The focus of this role is not server setup or hardware maintenance, but building robust pipelines, high-quality data models, and scalable transformation workflows. You will work closely with three data analysts and partner directly with departments like Marketing or Sales to ensure reliable, well‑structured datasets power reporting and analysis in Sigma.
Responsibilities Data Pipeline Development
Build and maintain ingestion pipelines from multiple sources, including: Aircall, HubSpot, Internal proprietary applications
Implement reliable, testable transformation workflows using SQL Mesh
Orchestrate and monitor jobs in Airflow
Ensure incremental, performance, and maintainable data pipelines
Data Modeling & Transformation
Design analytics‑ready data models in PostgreSQL
Develop clean, well‑documented dimensional models
Optimize queries and warehouse performance
Establish transformation best practices and review standards
Marketing Data Enablement
Work closely with Marketing stakeholders to understand attribution, funnel, campaign, and performance requirements
Translate business requirements into scalable data models
Prepare curated datasets for Marketing analysts
Required Qualifications
5+ years of experience in data engineering
Strong expertise in PostgreSQL (performance tuning, indexing, query optimization)
Hands‑on experience with Airflow for orchestration
Deep SQL knowledge and experience designing dimensional models
Experience working with transformation frameworks (SQLMesh, dbt, or similar)
Experience integrating SaaS tools such as HubSpot or Aircall into analytics environments
Strong stakeholder communication skills, especially with Marketing or Growth teams
Preferred Qualifications
Experience supporting BI tools such as Sigma
Background in marketing analytics (attribution, CAC, LTV, funnel analysis)
Experience working in analyst‑heavy teams
Familiarity with Python for pipeline utilities or automation
What Success Looks Like (2–5 Months)
Reliable ingestion from Aircall, HubSpot, and internal systems
Clear, governed marketing data models used consistently in Sigma
Noticeable improvement in query performance and data reliability
Reduced ad‑hoc firefighting and stronger pipeline observability
Analysts able to self‑serve confidently on curated datasets
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Boston, Massachusetts, United States

Compétences linguistiques

English

Avis aux utilisateurs

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