MO
Analytics Engineer transforming data into actionable insights for Moonpig Group's platform. Collaborating across departments to drive data - driven decisions with data transformation and engineering skills.
About the role
- You will deliver scalable, clean, documented models that abide by best practices and frameworks, helping to aid data discoverability, accessibility, maintenance, reporting and machine learning.
- You will be a key partner with data engineering, machine learning and data science teams, to translate technical requirements into non-technical outcomes and vice versa.
- You will optimise our reporting to reflect consistency in sources of truth, and align stakeholders in your domain on definitions of metrics and dimensions.
- You will act as translator between business and analyst requirements and applications to the data model.
- You will be a data steward, in charge of the governance, maintenance, and scalability of the data model you own, ensuring smooth communication of updates, changes, and downstream impact.
- You will be an expert in our data viz tool, error and data observability tooling, automation, ci/cd, iac, dbt and warehousing (glue/snowflake/spark), and understand and proselytize on best practices and standards when it comes to efficient querying, automation, and computational costs.
- You will practise design thinking when architecting data models, pipelines and automation.
- You will engage with both technical and non-technical stakeholders and team members to define and develop analytical solutions to drive the growth of the business or better attract and retain talent.
- You will collaborate with subject matter experts, data users, and other stakeholders to understand organizational processes and deliver relevant support which could range from dashboarding, data modeling, automation, computation at scale, ci/cd workflows, building agents and onboarding new users.
Requirements
- You can break down and explain complex processes, requirements and data architecture to both technical and non-technical stakeholders. You’ll have demonstrable experience in presenting these solutions to your peers.
- You have worked with multiple data visualisation and transformation tools, with preference for dbt, github, snowflake, airflow, airbyte, spark, terraform and looker or similar.
- You have extensive experience with data transformation using dbt, and are either certified or an expert in the tool and its standards.
- You will have extensive experience with data governance using a data catalog, semantic layer, FinOps, data observability and tuning AI tools to get the best from these practises.
- You are an expert in SQL and Python and are willing to upskill teams on best practices.
- You are at ease working with large and complex data sets and can speak to the fundamental problems with datasets that require extreme amounts of compute and storage.
- You will have a structured mindset and way of working that does not shy away from owning and leading projects using strong project management principles.
- You will have a working knowledge of design thinking & agile methodologies.
- Exposure to Version Control software such as git, including ci/cd workflows and best practises.
- Experience with data products used for machine learning systems and the backend and all the bells and whistles required to keep production systems live and healthy.
- **BONUS POINTS
- Knowledge of automation tools such as Streamlit
- Experience with AWS/GCP and all their offerings.
Benefits
- Medical, Dental, Vision, 401(k) match
- Unlimited Paid Time Off Policy
- Maven Fertility: $10,000 lifetime benefit for fertility, adoption, abortion care, and more.
- 26 Weeks Parental Leave: For both primary and secondary caregivers.
- Family & Compassionate Leave: Inclusive of domestic violence recovery.
- Company-wide Week Off: Annual collective rest for the entire company.
- Focus Fridays: No meetings, emails, or deadlines—just deep work.
Job title
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