The position

This is an exciting time to join Remote and make a personal difference in the global employment space as a Senior Analytics Engineer I, joining our Data Engineering team, composed of Analytics Engineers and Data Engineers. With the Data Analytics team, we support the decision making and reporting needs by being able to translate data into actionable insights to non-data professionals at Remote. We’re mainly using SQL, dbt, Python, Meltano, Airflow, Redshift, Metabase and Retool.

This role follows the Senior Engineer I role on the Remote Career paths.

Requirements

• 3+ years of experience in analytics engineering; high-growth tech company experience is a plus
• Strong experience using data transformation frameworks (e.g. dbt) and data warehouses (e.g. Redshift), strong proficiency in SQL
• Strong knowledge in data modelling techniques (Kimball, Data Vault, etc)
• Solid Experience with data visualization tools (e.g. Metabase)
• Strong affinity towards well crafted software - testing, knowledge of best practices, experience with CI/CD (e.g. Gitlab, Github, Jenkins)
• A self-starter mentality and the ability to thrive in an unstructured and fast-paced environment
• Proven collaboration and communication skills
• Experience in dealing with ambiguity, working together with stakeholders on taking abstract concepts and turning them into data models that can answer a variety of questions
• Writes and speaks fluent English
• It's not required to have experience working remotely, but considered a plus

Key Responsibilities

• DBT Modelling:
  • Design, develop, and maintain dbt (Data Build Tool) models for data transformation and analysis, providing clean and reliable data to end users enabling them to get accurate and consistent answers by self-serving on BI tools.
  • Collaborate with Data Analysts and Business Stakeholders to understand their reporting and analysis needs and translate them into DBT models.
  • Own our internal dbt conventions and best practices, keeping our code-base clean and efficient (including code reviews for peers).
• Data Analytics & Monitoring:
  • Ensure data quality and consistency by implementing data testing, validation and cleansing techniques.
  • Implement monitoring solutions to track the health and performance of the data present in our warehouse.
  • Train business users on how to use data visualisation tools.
• Drive our Culture of Documentation:
  • Create and maintain data documentation & definitions, including data dictionaries and process flows.
  • Collaborate with cross-functional teams, including Data Analysts, Business stakeholders, to understand their data requirements and deliver effective data solutions.
  • Share knowledge and provide guidance to peers, creating an environment that empowers collective growth.

Practicals

• You'll report to: Engineering Manager - Data
• Team: Data Engineering
• Location: Anywhere in the World
• Start date: As soon as possible

Application process

1. (async) Profile review
2. Interview with recruiter
3. Interview with future manager
4. (async) Small challenge
5. (async) Challenge Review
6. Interview with team members (no managers present)
7. Prior employment verification check(s)
8. (async) Offer