Edtech.com's Summary

Mighty Networks is hiring a Data Engineer, Foundations. This role involves designing and maintaining data pipelines that integrate multiple systems into a centralized warehouse, collaborating across functions to ensure timely and accurate data insights and promoting self-service analytics adoption.

Highlights

Design, build, and maintain data pipelines integrating product, marketing, CRM, and finance systems.
Develop and manage data models and transformations using dbt with clear documentation.
Implement and monitor data workflows using tools like Airflow and AWS Kinesis.
Use SQL (Postgres, Snowflake) and Python for analysis, validation, and automation.
Collaborate closely with engineers and business partners to improve data collection and accessibility.
Leverage AI-assisted tools for data discovery, documentation, code generation, and analytics automation.
Require 5+ years of data engineering experience with proficiency in modern data orchestration tools and cloud ecosystems.
Strong skills in data modeling principles and cross-functional communication.
Compensation ranges from $60,000 to $100,000 USD based on location and experience.
Work within the Engineering department and partner with product, marketing, and finance teams to drive a data-informed culture.

Data Engineer, Foundations Full Description

Empower every team to be data-informed — building trusted pipelines, self-service models, and a culture where data drives better decisions.

About Mighty Networks

Mighty Networks is on a mission to usher in the golden age of community.

Mighty enables entrepreneurs, brands, and non-profits to create the most valuable communities of real people meeting other real people in pursuit of results and transformation simply not possible on one's own.

In the past year, our customers (who we call Hosts) have generated $500M in revenue from their communities, courses, and events—including Tony Robbins, Deepak Chopra, Dr. Mark Hyman, The Home Edit, Yerba Madre, Mel Robbins, Marie Forleo, Matthew Hussey, Jefferson Fisher, Luvvie Ajayi Jones, The Luckiest Club, and The Budgetnista.

The Role

At Mighty Networks, we’re looking for a Data Engineer to join our growing Foundations organization.

In this role, you’ll design and maintain the data pipelines that connect our product, marketing, CRM, and finance systems into a unified warehouse — ensuring that every team has access to accurate, timely, and meaningful insights. You’ll collaborate deeply with engineers, analysts, and business partners to make data more accessible, self-service, and actionable.

What You’ll Do

Design, build, and maintain data pipelines that integrate multiple systems (application, marketing, CRM, finance) into a central data warehouse.
Develop and manage data models and transformations using dbt, ensuring clear lineage, testing, and documentation.
Implement and monitor data orchestration workflows (dbt, Airflow, or AWS tools like Kinesis) for reliability and freshness.
Partner with application engineers (e.g., in a Ruby on Rails environment) to define and capture analytics events and improve data collection.
Maintain data quality, consistency, and validation — identifying anomalies and ensuring trustworthy outputs.
Use SQL (Postgres, Snowflake) and Python for analysis, debugging, and automation.
Collaborate with third-party partners such as Sundial and data vendors to integrate external data sources effectively.
Drive adoption of self-service analytics, enabling product, marketing, and finance teams to independently explore and use data.
Champion data best practices — from documentation and transparency to governance and reproducibility.
Leverage AI-assisted tools for data discovery, documentation, and code generation to accelerate development and improve data quality.
Experiment with AI-powered analytics and automation to surface insights faster and enhance self-service data experiences across teams.

What We’re Looking For

5+ years of experience as a Data Engineer or similar role in analytics or data infrastructure.
Proven expertise with SQL (especially Postgres and Snowflake) for data modeling, validation, and analysis.
Experience with dbt and modern data orchestration tools (Airflow, AWS Kinesis, etc.).
Strong understanding of data modeling principles — fact/dimension design, normalization vs. denormalization, and schema optimization.
Proficiency in Python for data manipulation, testing, and pipeline automation.
Hands-on experience with AWS data tools and cloud-native data ecosystems.
Demonstrated ability to partner cross-functionally with engineering, analytics, finance, and marketing teams.
Excellent communication and documentation skills — able to make complex data systems understandable and accessible.
A rigorous, skeptical approach to data analysis: you validate, cross-check, and verify before drawing conclusions.
Curiosity about emerging AI technologies and how they can optimize data engineering workflows, analytics, and business intelligence.
Comfort using AI coding assistants or LLM-powered tools (e.g., for SQL generation, dbt documentation, or debugging) as part of your development process
Passion for building self-service data solutions that empower others to be data-informed.
Bonus: Experience integrating systems like HubSpot, Stripe, or marketing automation platforms.

Who You Are

You’re passionate about data integrity and clarity, and you believe good data work is about trust as much as technology.
You thrive on collaboration, working across teams to make sure everyone can use data effectively and confidently.
You enjoy bringing structure to chaos, automating the boring stuff, and building systems that scale gracefully.
You’re excited to explore how AI can elevate data engineering — from smarter transformations to predictive insights and automation.
You’re methodical and a bit skeptical — the kind of person who says “interesting” and then tries to falsify the result before celebrating an insight.
You have a growth mindset, love learning, and are eager to push the boundaries of what great data systems can do.
You take advantage of AI tools to develop efficiently and cross boundaries you couldn’t alone.
Finally, you’re a data culture advocate, helping others become more data-informed and driving the company toward better decision-making.

Compensation: The base salary for this role ranges from 60,000–$100,000 USD, with exact compensation based on location, experience, and cost of living.

Original Job Description

Empower every team to be data-informed — building trusted pipelines, self-service models, and a culture where data drives better decisions.

About Mighty Networks

Mighty Networks is on a mission to usher in the golden age of community.

The Role

At Mighty Networks, we’re looking for a Data Engineer to join our growing Foundations organization.

What You’ll Do

Design, build, and maintain data pipelines that integrate multiple systems (application, marketing, CRM, finance) into a central data warehouse.
Develop and manage data models and transformations using dbt, ensuring clear lineage, testing, and documentation.
Implement and monitor data orchestration workflows (dbt, Airflow, or AWS tools like Kinesis) for reliability and freshness.
Partner with application engineers (e.g., in a Ruby on Rails environment) to define and capture analytics events and improve data collection.
Maintain data quality, consistency, and validation — identifying anomalies and ensuring trustworthy outputs.
Use SQL (Postgres, Snowflake) and Python for analysis, debugging, and automation.
Collaborate with third-party partners such as Sundial and data vendors to integrate external data sources effectively.
Drive adoption of self-service analytics, enabling product, marketing, and finance teams to independently explore and use data.
Champion data best practices — from documentation and transparency to governance and reproducibility.
Leverage AI-assisted tools for data discovery, documentation, and code generation to accelerate development and improve data quality.
Experiment with AI-powered analytics and automation to surface insights faster and enhance self-service data experiences across teams.

What We’re Looking For

5+ years of experience as a Data Engineer or similar role in analytics or data infrastructure.
Proven expertise with SQL (especially Postgres and Snowflake) for data modeling, validation, and analysis.
Experience with dbt and modern data orchestration tools (Airflow, AWS Kinesis, etc.).
Strong understanding of data modeling principles — fact/dimension design, normalization vs. denormalization, and schema optimization.
Proficiency in Python for data manipulation, testing, and pipeline automation.
Hands-on experience with AWS data tools and cloud-native data ecosystems.
Demonstrated ability to partner cross-functionally with engineering, analytics, finance, and marketing teams.
Excellent communication and documentation skills — able to make complex data systems understandable and accessible.
A rigorous, skeptical approach to data analysis: you validate, cross-check, and verify before drawing conclusions.
Curiosity about emerging AI technologies and how they can optimize data engineering workflows, analytics, and business intelligence.
Comfort using AI coding assistants or LLM-powered tools (e.g., for SQL generation, dbt documentation, or debugging) as part of your development process
Passion for building self-service data solutions that empower others to be data-informed.
Bonus: Experience integrating systems like HubSpot, Stripe, or marketing automation platforms.

Who You Are

You’re passionate about data integrity and clarity, and you believe good data work is about trust as much as technology.
You thrive on collaboration, working across teams to make sure everyone can use data effectively and confidently.
You enjoy bringing structure to chaos, automating the boring stuff, and building systems that scale gracefully.
You’re excited to explore how AI can elevate data engineering — from smarter transformations to predictive insights and automation.
You’re methodical and a bit skeptical — the kind of person who says “interesting” and then tries to falsify the result before celebrating an insight.
You have a growth mindset, love learning, and are eager to push the boundaries of what great data systems can do.
You take advantage of AI tools to develop efficiently and cross boundaries you couldn’t alone.
Finally, you’re a data culture advocate, helping others become more data-informed and driving the company toward better decision-making.

Compensation: The base salary for this role ranges from 60,000–$100,000 USD, with exact compensation based on location, experience, and cost of living.

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Data Engineer, Foundations

Edtech.com's Summary

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