Analytics Engineer - Python/SQL

Description

Immediate Joiners Preferred.

Were hiring Analytics Engineer to help build the data foundation at Heaptrace.

This is a high-impact, early role where youll shape how data is modeled, transformed, and consumed across the company.

Youll turn raw product and business data into trusted, well-modeled datasets that power dashboards, reporting, and analysis.

This role is ideal for someone who enjoys building from first principles, cares deeply about data quality and usability, and wants ownership over core data infrastructure.

What Youll Do

• Design and build analytics-ready data models(facts, dimensions, metrics)that support product, growth, and business reporting.
• Transform raw data into clean, well-documented analytics tables using modern data tooling (e. dbt-style workflows).
• Define and implement metrics and business logic (e. activation, conversion, retention, churn) as reusable data models.
• Partner with stakeholders to understand reporting needs and translate them into scalable data structures.
• Build the foundation for automated reporting and dashboards used by teams across the company.
• Establish data modelling best practices, naming conventions, and documentation.
• Improve data reliability through testing, validation, and monitoring.
• Collaborate with Engineering to ensure data sources are reliable and analytics-friendly. Help shape the long-term data architecture and analytics strategy.

What Were Looking For

• 3+ years of experience in analytics engineering, data analytics, or data engineering.
• Strong SQL skills and experience modelling data for analytics and reporting.
• Experience working with modern analytics stacks (e. dbt, Python, Hex, Air byte etc.
• Solid understanding of dimensional modelling, metrics design, and analytical best practices.
• Comfortable working with imperfect data and iterating toward better systems.
• Strong communication skills able to explain data concepts to non-technical partners. Self-directed and excited to take ownership in an early-stage environment.

Nice To Have

• Experience being an early data hire or building analytics foundations from scratch.
• Familiarity with SaaS metrics (trials,subscriptions, usage, retention, churn). Experience partnering closely with Product or Growth teams.

(ref:hirist.tech)