Offer summary
Qualifications:
3+ years experience as Data/Analytics Engineer, Proficiency in Python and SQL, Git knowledge.Key responsabilities:
- Build and optimize data models using Python, SQL
- Develop data processes, quality procedures, governance
Match score not available
Priority access
Match score not available
Data/Analytics Engineer - Python, Postgres, SQL
72% Flex
Job description
Your missions
About Ruggable
Founded in 2017 and headquartered in Gardena, California, Ruggable is the first patented machine-washable rug that combines beauty and utility to bring comfort and style to your home.
About The Role
As a Data Engineer at Ruggable, you will own, contribute, and extend the business’s data pipelines by cleansing, standardizing, modeling, and transforming source data into usable data marts. You will be a key part of a team whose goal is to build and maintain foundational data infrastructure essential to driving Ruggable’s revenue growth and accelerating user acquisition. You will work closely with technology leadership, data engineers, data analysts, data scientists, and engineering teams to build best-in-class data models and processes that stitch together complex sets of data stores and drive actionable insights.
What You’ll Do
Founded in 2017 and headquartered in Gardena, California, Ruggable is the first patented machine-washable rug that combines beauty and utility to bring comfort and style to your home.
About The Role
As a Data Engineer at Ruggable, you will own, contribute, and extend the business’s data pipelines by cleansing, standardizing, modeling, and transforming source data into usable data marts. You will be a key part of a team whose goal is to build and maintain foundational data infrastructure essential to driving Ruggable’s revenue growth and accelerating user acquisition. You will work closely with technology leadership, data engineers, data analysts, data scientists, and engineering teams to build best-in-class data models and processes that stitch together complex sets of data stores and drive actionable insights.
What You’ll Do
- Build processes supporting data transformation, data quality, data modeling, and data governance.
- You will be responsible for developing and optimizing fact and dimension data models, data mart data models, and Looker back-end data models.
- Utilize your in-depth knowledge of Data Modeling best practices (Kimball, Star/Snowflake schemas, Fact & Dimension modeling) to build out a foundational data model.
- Promote Analytics Engineering best practices within the team while mentoring others.
- Develop highly scalable data models in dbt (Python & SQL) to organize data from various source systems and meet downstream stakeholder use cases, use Apache Airflow to orchestrate, schedule and monitor the workflows, and build out new data marts in Looker using LookML.
- Minimum of 3+ years relevant experience as an Analytics Engineer and/or Data Engineer
- Proficiency in scripting languages like Python
- Familiarity with version control systems such as Git
- Deep understanding of SQL with relational data stores and column-oriented database systems such as Redshift, Postgres, and CockroachDB
- Ability to interact cross-functionally with non-technical departments
- Ability to work individually or as part of a team
- Support and expand standards, guidelines, tooling, and best practices for analytics engineering
- Experience with data modeling best practices (fact/dimension)
- Experience with extensive data QA/validation (root cause analysis) Preferred:
- Experience with AWS or relevant cloud tools
- Familiarity with data warehousing concepts and technologies
- Experience with workflow and orchestration management tools like Airflow.
- Knowledge of BI Tools like Tableau, Looker, etc
- Experience with reporting migrations/system migrations (model refactoring, validation, root cause analysis)
- Working knowledge of API integration or Stream-based data extraction and structured, semi-structured and unstructured file formats (understand upstream processes)
Required profile
Experience
Level of experience: Mid-level (2-5 years)
Spoken language(s):
English
Check out the description to know which languages are mandatory. Soft Skills
- Team Collaboration
- Mentoring
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