We are seeking a versatile and data-driven professional for a high-impact Analytics Engineering role within our E-commerce Analytics team. This is a hybrid position that bridges the gap between data engineering and business analysis, perfect for a candidate with a strong technical foundation who is passionate about enabling data-driven decisions. You will be responsible for building and managing the critical data infrastructure and models that power our analytics and business intelligence capabilities.

The ideal candidate has deep expertise in SQL and Python and enjoys not just building robust data solutions but also understanding the 'why' behind the data. You will work side-by-side with analysts to transform raw data into curated, analysis-ready datasets that drive our product and business strategy.

Key Responsibilities :

- End-to-End Data Modeling : Partner with business team to translate business requirements and key metrics (e.g., user journeys, conversion funnels) into scalable and reliable data models in Snowflake/BigQuery.

- Develop & Maintain Data Pipelines : Build, maintain, and optimize robust ELT/ETL pipelines using SQL and Python to ensure the timely and accurate flow of data.

- Codify Business Logic : Act as the owner of our analytics data layer. Develop and codify key business logic and metrics, ensuring that our data is consistent, trusted, and easy to understand across the company.

- Enable Business Intelligence : Engineer and manage the data sets that power our dashboards in Looker, focusing on performance, usability, and empowering self-service analytics.

- Ensure Data Quality & Governance : Implement data quality checks, testing, and documentation to maintain the integrity and reliability of our analytics ecosystem.

- Technical Collaboration : Serve as the technical expert within the analytics team, providing guidance on data architecture and promoting best practices in data usage and querying.

- Ensure data quality, integrity, and adherence to data governance standards

Technical Proficiency :

- SQL and Database Management : Expert-level SQL for both complex data transformation/modeling and analytical querying within a cloud data warehouse (Snowflake, BigQuery).

- Programming : Strong proficiency in Python for building data pipelines and automating data workflows.

- BI & Data Modeling : Proven experience building the data models that power BI tools (e.g.,Looker, Tableau). Experience with LookML or similar semantic layer technologies is a major plus.

- Modern Data Stack : Hands-on experience with modern data engineering tools. Experience with dbt is highly desirable.

- Software Engineering Practices : Solid understanding of version control (Git) and CI/CD principles.

Business Acumen & Analytical Mindset :

- Product Sense : A strong understanding of and curiosity for product metrics, user journey analysis, and conversion funnels in an e-commerce context.

- Strategic Thinking : Ability to translate business needs into technical specifications and align your work with broader analytics and product goals.

- Communication & Collaboration : Excellent ability to communicate complex technical concepts to both technical and non-technical stakeholders, fostering a strong partnership with the analytics team.

- Problem-Solving : A creative and analytical approach to solving complex data challenges and building efficient, scalable solutions.

Nice to Have :

- Experience modeling data from various online marketing channels (e.g., Paid Search, SEO, Email).

- Familiarity with marketing analytics concepts like attribution modeling or cohort analysis.

The job is for:

May work from home