Data Engineer (Remote)

FLOURISH; Snowflake (AZ); Remote; USD 80,000 - 130,000; Full time

Job summary

Join a forward-thinking company as a Data Engineer, where you'll play a crucial role in evolving data infrastructure for the cannabis industry. This innovative firm is looking for someone to transform transactional data into insightful analytics using cutting-edge tools like Snowflake and Sigma Computing. You'll collaborate with teams to design data architecture, ensure data integrity, and implement CI/CD pipelines, all while working in a remote-first environment. If you're passionate about data engineering and eager to explore advanced solutions, this opportunity is perfect for you!

Qualifications

• Experience with cloud-based data warehousing technologies is essential.
• Strong SQL skills and knowledge of ETL/ELT tools are required.

Responsibilities

• Engineer and maintain a data warehouse for client-facing analytics.
• Develop and optimize ETL processes for data transformation.

Skills

AWS Redshift

Snowflake

Google BigQuery

SQL

dbt

Apache Airflow

Talend

Informatica

Sigma Computing

Python

Tools

CI/CD pipelines

AWS services

Terraform

Ansible

Job description

Data Engineer - Flourish Software (Remote)

About Us

Flourish Software is a leading cannabis supply chain and retail software company. We are working to empower the cannabis industry through better technology.

What’s the opportunity?

As a Data Engineer at Flourish Software, you will be instrumental in evolving our data warehouse to enable embedded analytics for our clients. You’ll transform transactional data into a structure optimized for business intelligence and reporting, with Sigma Computing as our primary BI tool. Currently, we have a foundational data warehouse and a SQL-driven ETL process, and we’re looking to explore advanced solutions, including Snowflake, to enhance our data infrastructure. If you have experience building scalable data warehouses and are excited about exploring new tools and database options, this role is for you!

What do we value?

• Honesty, integrity, and self-driven motivation
• Clean, readable code and well-thought-out solutions
• Thorough planning prior to execution
• Teamwork and communication
• Happiness and satisfaction in your work

Key Responsibilities:

• Engineer, build, and maintain a data warehouse to transform transactional data into a client-facing analytics structure.
• Develop and optimize ETL/ELT processes to support data transformation and integrity for embedded analytics.
• Collaborate on BI and reporting initiatives, supporting advanced data visualization with Sigma Computing.
• Explore and evaluate new data warehousing solutions, including Snowflake, to improve data accessibility and scalability.
• Partner with product and engineering teams to define data architecture and best practices for reporting.
• Ensure data security, compliance, and governance across data systems.
• Implement and maintain CI/CD pipelines to automate data workflows and enhance system reliability.

Skill Requirements

• Experience with cloud-based data warehousing technologies, especially AWS Redshift, Snowflake, or Google BigQuery.
• Knowledge of data modeling techniques, including dimensional modeling and star schema.
• Strong SQL skills for data transformation, cleaning, and loading.
• Familiarity with ETL/ELT tools such as dbt, Apache Airflow, Talend, or Informatica for pipeline orchestration and automation.
• Proficiency with BI tools, especially Sigma Computing, and similar tools like Looker, Tableau, or Power BI.
• Understanding of data structuring for analytics and reporting.
• Hands-on experience with AWS services, including Lambda, Glue, Athena, Redshift, RDS, and S3.
• Experience with a programming language such as Python or Scala for data manipulation and pipeline development.
• Experience implementing data governance frameworks, security best practices, and knowledge of SOC 2 or ISO 27001 compliance standards.
• Ability to work independently in a remote-first environment and manage time effectively.
• Availability to work in US time zones.
• Excellent written and verbal communication skills in English.

Nice to Have

• Proficiency in infrastructure-as-code tools like Terraform and Ansible.
• Linux administration skills and familiarity with shell scripting.
• Familiarity with machine learning tools such as scikit-learn or AWS SageMaker, particularly for predictive analytics and forecasting.
• Knowledge of DataOps best practices, including CI/CD for data workflows, with tools like Apache Airflow, Dagster, or Prefect.
• Prior experience in the cannabis or retail industry.

Salary Range

• US-Based Candidates: $80,000-$130,000, depending on experience.
• Candidates outside the US: Compensation will be adjusted based on local market rates, typically ranging from $50,000- $80,0000 USD per year.