Analytical Data Engineer (Contract)

United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Financial ServicesIndustries

Requirements

Candidates should possess 5-7 years of experience with cloud data warehouses, including at least 3 years of hands-on experience with Snowflake. A minimum of 4 years in data engineering, analytics engineering, or a similar data-focused role is required, along with a strong understanding of data warehousing concepts like Star/Snowflake schemas, slowly changing dimensions, and data marts. Proficiency in SQL, including advanced joins, CTEs, and window functions, is essential, as is experience with Python for data manipulation, ingestion, and API integrations. Familiarity with workflow orchestration tools such as Airflow and the ability to work independently and communicate effectively with technical and non-technical stakeholders are also necessary.

Responsibilities

The Analytical Data Engineer will design and maintain scalable, business-friendly data models and curated datasets in Snowflake. They will build and optimize data pipelines and transformations using SQL and Python, and develop reusable data assets like views and table functions for self-service analytics. This role involves partnering with data architects, data scientists, business intelligence analysts, and stakeholders to capture business rules and requirements. Responsibilities also include developing and orchestrating workflows in Airflow to ensure reliable, automated data delivery, diagnosing and resolving data issues by tracing SQL lineage, and collaborating with teams to translate business requirements into effective data structures. Additionally, the engineer will implement proactive data validation, quality checks, and monitoring, document data models and lineage, automate data enrichment and integration workflows, and continuously evaluate and improve data infrastructure while staying current with emerging data tools and practices.

Skills

Data Modeling

Data Pipelines

SQL

Python

Snowflake

Data Quality

Data Governance

ETL

Data Transformation

Business Intelligence

Data Analysis

Motley Fool

Provides investment advice and financial education

About Motley Fool

The Motley Fool offers financial services focused on helping individual investors make informed decisions about their money. It provides premium subscription services like Stock Advisor and Rule Breakers, which deliver stock recommendations and investment advice to assist clients in building and managing their investment portfolios. The company generates revenue through subscription fees, website advertising, and affiliate partnerships. Unlike many competitors, The Motley Fool emphasizes a long-term investment philosophy and prioritizes financial education, catering to both novice and experienced investors. Its goal is to enhance financial literacy and empower individuals to achieve smarter, happier, and wealthier lives.

Alexandria, VirginiaHeadquarters

1993Year Founded

$54.2MTotal Funding

LATE_VCCompany Stage

Fintech, Financial ServicesIndustries

501-1,000Employees

Risks

Teads acquisition may lead to integration challenges and cultural clashes.

Cannabis facility investment involves regulatory risks and market volatility.

$5 million Bitcoin investment exposes the company to cryptocurrency market volatility.

Differentiation

The Motley Fool offers a unique blend of financial education and investment advice.

It provides premium subscription services like Stock Advisor and Rule Breakers.

The company champions shareholder values and advocates for individual investors.

Upsides

Increased interest in financial literacy boosts demand for The Motley Fool's services.

The rise of retail investors expands the audience for subscription services.

AI integration allows for personalized investment advice and improved user experience.

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