Formative is seeking a Lead Analytics Engineer to join their data team. The role involves applying data engineering best practices to analytics code, providing clean data sets to end users, conducting code reviews, and transforming raw data into business insights.
Responsibilities:
- We are looking for a Lead Analytics Engineer to join our data team
- Reporting to the Hiring Manager, you will be responsible for applying data engineering best practices to analytics code to transform, test, and document data
- You will provide clean and organized data sets to end users
- You will be provide expert code reviews and mentorship to other engineers in the data space
- You will be responsible for building and maintaining composable data models, as well as optimizing SQL query performance for the models you build
- You will transform raw data into business insights, working closely with stakeholders and developing analyses to answer critical business questions
- You will create data visualizations and help stakeholders explore and understand the data visualization tools available to them
- Build new analyses and support existing ones using SQL and Python
- Apply software engineering principles like version control and continuous integration to the analytics codebase
- Expand our data warehouse with clean data ready for analysis
- Apply advanced data testing strategies to ensure resulting datastores are aligned with expected business logic
- Implement validation checks and automated testing procedures to manage data quality in your ETL/ELT pipelines
- Work with stakeholders to define business logic and data expectations
- Help drive a change in the usage of data by actively surfacing insights to stakeholders
- Lead initiatives and problem definition, scoping, design, and planning
- Build tools and automation to run data infrastructure
- Manage large-scale data migrations in relational datastores
Requirements:
- 8+ Years experience working with data in a software environment
- Mastered proficiency in SQL and Python
- Advanced experience managing business semantic layer tooling, data catalog tooling and data integrity testing frameworks
- Experience with dbt orchestration and best practices
- A track record of working autonomously and proactively, with deep domain knowledge of data systems
- Required Tech Stack: SQL, Python, relational datastores, DAG tooling (like Dagster or Airflow), dbt and Tableau
- Experience with cloud-based infrastructure (AWS, GCP, Terraform) and document, graph, or schema-less datastores