What we're looking for:
InStride is seeking an experienced Analytics Engineer to join our growing Data Analytics team. As an Analytics Engineer, you will play a pivotal role in building and optimizing the dimensional data models in Databricks. This role reports to the Director, Data Analytics and will work closely with business leaders, analysts, and data engineers to design and implement robust, scalable data structures that support our BI tools and deliver meaningful insights.
Your work will include ingesting data from a variety of sources, many of which are not traditional application data sources. You will also need a deep understanding of data security, data modeling, Python, SQL, and BI tools like Tableau, as well as expertise translating a complex business model to actionable data and insights.
Skills we’d love to see you show off:
- Dimensional Data Modeling: Design, build, and optimize the gold layer in Databricks, creating dimensional models that support business reporting and analytics. Ensure these models are scalable, performant, and aligned with the company’s data strategy.
- Data Ingestion & Integration: Ingest data from various sources, including non-application data sources, using SQL and Python to clean, transform, and load data. Data pipelines should be reliable, efficient, and adhere to best practices for data security and governance
- Cross-Team Collaboration: Work closely with business leaders, analysts, and data engineers to understand data requirements, define key business metrics, and develop data models that meet the needs of various stakeholders.
- Business Insights Support: Build and maintain data models and Tableau dashboards, enabling stakeholders to self-serve insights and make data-driven decisions.
- Performance Optimization: Monitor and optimize ETL processes and data models for performance, ensuring timely access to key data sets and insights.
- Documentation & Best Practices: Maintain comprehensive documentation of data models, pipelines, and business rules. Use GitHub for version control and to back up all code, ensuring proper documentation, collaboration, and traceability. Promote best practices across the team to ensure consistent, high-quality output and streamline collaboration.
- Support Advanced Analytics: Collaborate with data analysts and engineers to enable more advanced analytics use cases, such as predictive modeling or trend analysis.
Who you are:
- 5+ years of experience in data engineering or a highly technical analytics role, where you worked extensively with data modeling and business intelligence tools.
- 5+ years of experience working in a fast-paced environment.
- You thrive in a fast-paced environment and enjoy the challenge of working independently on complex tasks while proactively seeking feedback and improvement.
- You’re passionate about education and driven to make learning more accessible. If you have prior experience in edtech or education, that’s a big plus!
- You have a keen understanding of business logic and can quickly grasp complex relationships between data and business operations.
- You are a team player who excels at working with both technical and non-technical stakeholders, advising them on best practices and how to best leverage data to drive decisions.
- You have a proactive approach, constantly seeking out new ways to improve processes, tools, and models for the benefit of the entire organization.
How you will create impact:
- You will create a single source of truth across the company by building and maintaining a centralized data reporting layer that supports all business functions, including marketing, sales, finance, and product.
- Your work will enable the creation of dynamic, data-driven Tableau dashboards that provide key stakeholders with the insights they need to drive business decisions.
- You will help ensure data accuracy, consistency, and reliability across the organization, which will foster greater trust in the data used for decision-making.
- You’ll be key in ensuring that the company’s data infrastructure scales efficiently as it grows, building data models that are not only accurate but also scalable and future-proof.
