Offer summary

Qualifications:

Minimum 5 years of experience in analytics engineering, data modeling, or data warehousing., Proficiency in SQL, preferably Postgres, and Python; experience with Scala or R is a plus., Experience with modern data stack tools such as Snowflake, BigQuery, Airflow, Looker, and Tableau., Strong understanding of software engineering best practices, including version control, testing, and CI/CD..

Key responsibilities:

Design, build, and maintain data models and SQL pipelines to standardize metrics.

Create scalable and reliable data models that balance performance and business needs.

Collaborate with analysts and stakeholders to develop datasets supporting business reporting.

Document processes and lead knowledge-sharing sessions to improve data literacy.

Job description

Job Title: Analytics Engineer
Location: Remote (CST Time Zone)
Salary Range: up to 5000 USD

Work Schedule: Monday - Friday, 9:00 AM to 5:00 PM (CST)

NOTE: INDEPENDENT CONTRACTOR POSITION

Company Overview:

Sagan is an exclusive membership community for top executives, founders, and CEOs seeking to hire and maximize the impact of international talent. We bridge the gap between global talent and US-based businesses, connecting candidates from vibrant regions like Latin America, the Philippines, India, Pakistan, Bangladesh, and Africa with leading American companies. Sagan provides a high-performance remote work environment, ensuring access to world-class opportunities for top-tier professionals.

About the Company:

Sagan represents a growing US-based company that is data-driven and product-focused, with a strong emphasis on analytics to inform strategy. The internal culture values systems thinking, cross-team collaboration, and high data integrity.

Position Overview:

We're hiring an experienced Analytics Engineer to design, build, and maintain trusted data models that power business decisions. As our first hire in this function, you'll be the bridge between engineering and analytics, creating scalable, reliable datasets and defining data best practices across the organization. This is an ideal opportunity for someone passionate about improving data quality, accessibility, and enablement.

Key Responsibilities:

Own the transformation layer: Develop and maintain data models, SQL pipelines, and semantic layers that standardize metrics across teams.
Model for reliability and scale: Design data models that balance performance, maintainability, and business needs.
Enable self-serve analytics: Partner with analysts and stakeholders to define datasets that support business reporting without constant engineering support.
Document and educate: Write clear documentation and lead knowledge-sharing sessions to improve data literacy.
Improve data quality: Build tests, monitors, and workflows to ensure accuracy and consistency.
Collaborate cross-functionally: Work closely with engineering, product, and business teams to align on metrics, schemas, and definitions.

Qualifications:

5+ years of experience in analytics engineering, data modeling, or data warehousing.
Strong SQL (Postgres preferred) and Python (preferred), Scala, or R.
Experience with modern data stacks such as Snowflake, BigQuery, Airflow, Looker, and Tableau.
Familiarity with software engineering best practices (version control, testing, CI/CD).
Ability to translate complex business needs into scalable technical solutions.
Strong written and verbal communication skills.
Collaborative mindset and ability to work cross-functionally.

Nice-to-Haves: