Mid-level Data Engineer

Blue Orange Digital

. Build and maintain staging and intermediate dbt models in a medallion architecture .

Posted 10/8/2026part-timeRemoteJuniorMid-Level💰 $3,500 - $5,000 per monthWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining dbt models within a medallion architecture, ensuring data quality and integrity through rigorous testing and documentation. Proficient in SQL and familiar with cloud data warehousing solutions, with strong communication skills for effective collaboration in a remote environment.

Highest-signal resume keywords

Data Engineering ExperienceSQL ProficiencyDbt KnowledgeSnowflake ExperienceGit and GitHub Workflows

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLDbt ModelsEntity Resolution LogicSchema ValidationDimensional ModelingData Quality TestingPythonJinja TemplatingAI-Powered Tagging ModelsBridge Tables

Soft Skills

Strong Written EnglishReliable Async Communication

Tools & Technologies

SnowflakeDbt CloudGitGitHub

Industry Keywords

Medallion ArchitectureData Quality IssuesInvestment DataFinancial DataAlternative Data

Tech Stack

Tools & technologies

Amazon RedshiftBigQueryCloudPythonSQL

About the role

Key responsibilities & impact

Build and maintain staging and intermediate dbt models in a medallion architecture
Implement entity resolution logic using ID and bridge tables for companies, contacts, and deals
Implement and maintain AI-powered tagging models using Snowflake Cortex
Flag data-quality issues for review
Write schema validation, row-count, nullability, and uniqueness tests for models
Maintain source-system bridges and lookup tables
Adapt models when upstream systems change
Keep source YAML documentation current, including lineage, freshness expectations, and schema notes
Monitor dbt Cloud jobs
Debug failed runs and investigate data inconsistencies, escalating when needed
Submit clean, well-documented pull requests for senior review
Work with a senior engineer who scopes the work, while progressively taking on more ownership

Requirements

What you’ll need

2–4 years of data engineering experience in a production environment
Solid SQL: multi-stage CTEs, window functions, and well-optimized queries
Working knowledge of dbt: models, tests, sources, and basic macros
Experience with Snowflake or a similar cloud data warehouse (BigQuery, Redshift, Databricks)
Comfort with dimensional modeling and layered (medallion) architectures
Git and GitHub workflows: branching, pull requests, and code review
Strong written English and reliable async communication with a remote US-based team
Availability at least 20 hours per week, with at least 4 hours of overlap with US Eastern time (Mon–Thu)
Resume and all application materials must be submitted in English
Python for data validation or transformation logic (nice to have)
dbt macros and Jinja templating (nice to have)
Exposure to investment, financial, or alternative data (nice to have)

Benefits

Comp & perks

Flexible part-time schedule
Fully remote
Hands-on work in a mature, production dbt and Snowflake codebase, including AI-powered models
Mentorship from senior data engineers and a clear path to more ownership
Builder culture where engineers lead and ship
Work on diverse, challenging projects across industries
Flexible Schedule
Unlimited Paid Time Off (PTO)
Paid parental/bereavement leave
Worldwide recognized clients to build skills for an excellent resume
Top-notch team to learn and grow with