Analytics Engineer
Il y a 6 mois
Everything we do is for our customers, and we’re currently serving over 12,000+ ecommerce merchants, including : Steve Madden, Timbuk2, Decathlon, and Sports Illustrated. They love us for our innovative product, our focus on their ecommerce needs, and, of course, our lightning-fast customer service response time.
We raised $25 million in our Series B round in December 2020 and $30 million in our Series C round in 2022. We more than doubled in size in every meaningful way: annual recurring revenue, the size of our customer base, and the size of our Gorgias team, for starters.
We’re still growing fast and looking for new teammates who want to grow with us.
**About the Data Analytics team**:
- Data Analytics is a cross-functional team that works hand-in-hand with all of the other business teams (Go-to-market Marketing, Sales, Success & Support, Product) and also interacts with the dev teams.
- Our core role is to ensure that data flows accurately and efficiently across all of these teams and the tools they use to maintain and improve our data stack.
- In addition to this, we build complex data models and perform data analysis to provide insights.
- The Data Analytics team is also in charge of building data products that maximize each team's efficiency: lead qualification models, optimizing deal routing, predicting churn, automated lead enrichment, etc.
The team itself is composed of two sub-teams:
- ** Business Intelligence** helps the rest of the company by providing insights into performance and by giving them the resources needed to achieve their goals. This includes things like providing or editing data marts, helping build dashboards, and more.
- ** Analytics Engineering** is responsible for the management and maintenance of the Data Platform, including all data pipelines and assets. Their primary goal is to ensure that accurate and easily accessible data is provided at scale to end users. They also play a key role in advising and training Data Analysts on analytics best practices and maintaining up-to-date documentation and knowledge sharing.
If you are naturally data curious, excited by high-quality data modeling, experienced in improving the availability and usability of datasets, and motivated by having an impact on the business where you work, we want to hear from you.
**What You'll Do**:
You will join our Analytics Engineering section and will be integral to building out our world-class data products and enabling all teams across the company to move faster and smarter.
You will work on the analytics code base ensuring high data quality, availability, and performance to support Data Analysts.
- Design and implement data models that organize and structure data for analytical purposes.
- Ensure that data is clean, well-structured, and ready for visualization, exploration, and analysis.
- Implement data monitoring and alerting systems to proactively identify and address data issues.
- Create and maintain documentation that enhances understanding and utilization of data assets.
- Share knowledge with team members to promote a data-driven culture within the organization.
**Who You Are**:
- You have 3+ years of hands-on experience as an analytics engineer or equivalent.
- 3+ years of experience in data modeling and data warehouse architecture, with solid SQL experience. **You care about writing good and clean SQL**, with an emphasis on readability and performance.
- 2+ years of experience with the modern data stack (ETL / Warehouse / dbt / BI/documentation), creating data products within a data warehouse environment to meet business goals.
- You have a **natural fit for both technical and business challenges**. We are building technical solutions to solve business-oriented challenges, so strong business acumen is needed for the role.
- You are always learning and staying informed about new tools and practices. At the speed at which the ecosystem is evolving, it is essential to stay on top of things and always look for new ways to improve our work.
- You love working with a wide range of data sources and stakeholders from operational and product teams.
- You pay attention to detail, with strong organization and prioritization skills, comfortable switching gears and moving between projects seamlessly.
**Our current data analytics stack mainly includes**:
- The tools you’ll be using are in bold_
- ** Storage: BigQuery**
- ** Transformation: DBT**
- ** BI tools: Periscope**
- ** Data Activation: Hightouch, Segment**
- ** Data Monitoring: Datafold, Metaplane**
- ** Project management: Linear, Notion**
- Data ingestion: Airbyte, Segment, Fivetran
- GCP products (Compute Engine, Cloud Functions, Cloud Run, PubSub...)
- CI/CD: GitHub Action & GitLab
**The position's Interviewing Process**:
- Initial call with a recruiter that will present Gorgias, the team, and the position in more detail - ask all the questions you need
- Meet your manager, Elliot, Data Analytics Manager: get to know each oth
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