Job description
Minimum 5+ years working experience as a data or software engineer in a fast-paced growing company. Excellent SQL and Python knowledge strong hands-on data modeling and data warehousing skills and experience in transformations orchestrated through technologies such as dbt/cloud data flow would be a plus. Strong experience applying software engineering best practices to analytics (e.g. version control, testing, and CI/CD)
Must have Skills:
- Technical Proficiency:Possess excellent SQL and Python skills, with hands-on experience in data modeling and data warehousing. Knowledge of technologies like dbt/cloud dataflow is a plus.
- Best Practices:Strong experience applying software engineering best practices to analytics, including version control, testing, and CI/CD.
- Cloud Expertise:Power-user and expert in building scalable data warehouses and pipelines using cloud tools such as Snowflake, AWS, Google Cloud, and Cloud ETL tools like Databricks (Spark/Azure).
- ETL/ELT:Solid experience with ETL/ELT processes, scheduling tools (e.g., Talend, Airflow), and API management tools.
- Data Familiarity:Experienced with customer, marketing, and/or web data sources (e.g., Salesforce, Google Analytics, Ad Words, YouTube).
- Visualization:Proficient with data visualization tools and packages such as Looker, Tableau, and matplotlib.
- Attention to Detail:Strong attention to detail to identify and address data quality issues.
- Traits:You re a self-starter, motivated, responsible, innovative, and technology-driven individual who excels both independently and as part of a team.
- Communication:A proactive problem solver with excellent communication and project management skills, able to convey findings and solutions to technical and non-technical audiences.
Key Responsibilities:
- Requirements Gathering:Work closely with data users to understand business requirements.
- Data Modeling:Design high-performance, reusable, and scalable data models for our data warehouse to ensure consistent and reliable answers for end-users.
- Data Transformations:Write complex yet optimized data transformations in SQL/Python using dbt or similar technology.
- Data Management:Continuously discover, transform, test, deploy, and document data sources.
