Senior Data Engineer (Data Mgmt and Reporting)

Senior Data Engineer (Analytics, Reporting & Data Management)

Global / Remote (1099 Contractor, Full-Time)

DMD Solutions is proud to be partnering with Foundations United in the search for a Senior Data Engineer (Analytics, Reporting & Data Management). Foundations United is building a connected ecosystem of DAOs and blockchain-native products that redefine how communities collaborate, govern, and create.

In this role, you will own the organization, quality, and usability of our data. Reporting to the Head of Data, you will design analytics pipelines, build trusted reporting, and ensure data is well-structured, documented, governed, and easy to use across the ecosystem.

This role is ideal for someone who is not just great at building dashboards—but who cares deeply about clean data, clear definitions, and long-term maintainability.

Key Responsibilities

Data Organization & Management (Core Ownership)

• Own how data is structured, named, documented, and organized across warehouses, schemas, and datasets.
• Establish and maintain clear data models, naming conventions, and metric definitions.
• Ensure data is discoverable and understandable for analysts, product teams, and leadership.
• Partner with the Head of Data to enforce lightweight governance and access standards.

Analytics Engineering & Reporting

• Own core reporting datasets, KPIs, and metrics used across the business.
• Design analytics-ready data models to support dashboards and self-service reporting.
• Build and maintain dashboards and recurring reports used by leadership and product teams.
• Ensure consistency of metrics across brands, DAOs, and products.

Data Pipelines & Transformations

• Build and maintain ETL/ELT pipelines that transform raw data into clean, analytics-ready tables.
• Implement transformation logic, testing, and documentation to ensure correctness and trust.
• Optimize queries and transformations for performance and cost.

Data Quality, Trust & Reliability

• Own data quality checks, freshness validation, and reporting SLAs.
• Proactively identify data issues and resolve them before they impact decision-making.
• Monitor pipelines and datasets to ensure reliability and accuracy.

Stakeholder Partnership & Analysis

• Partner with product, finance, operations, and leadership to understand reporting needs.
• Translate business questions into clean datasets, metrics, and analyses.
• Guide stakeholders on correct data usage and interpretation.

Tooling, Documentation & Enablement

• Maintain documentation for datasets, metrics, and reporting logic.
• Enable self-service analytics while protecting data quality and consistency.
• Use modern analytics tooling (e.g., Snowflake, BigQuery, Redshift, dbt, Looker, PowerBI).

Required Qualifications

• 5+ years of experience in data engineering, analytics engineering, or data-focused roles.
• Proven experience organizing and managing production data (schemas, models, metrics).
• Strong experience building reporting pipelines, dashboards, and analytics models.
• Advanced SQL and strong Python skills for data transformation and analysis.
• Experience with cloud data warehouses and analytics tools.
• Demonstrated ownership of data quality, documentation, and metric definitions.
• Strong communication skills and comfort working directly with non-technical stakeholders.

Preferred Qualifications

• Experience with Web3, blockchain, or crypto-native data.
• Experience with dbt or similar analytics transformation frameworks.
• Background in finance, product, or operational analytics.
• Experience in startup or high-growth, ambiguous environments.

What We Offer

• Fully remote, async-first team culture.
• Clear ownership of analytics, reporting, and data organization.
• Competitive contractor compensation with potential token incentives.
• Direct partnership with the Head of Data.
• Opportunity to help bring order and clarity to a growing Web3 data ecosystem.

Application Requirement

Please include examples of:

• Reporting or dashboards you’ve owned
• Analytics models or metrics frameworks you’ve designed
• How you organized, documented, or improved data usability in prior roles