Analytics Lead, Full Stack (Strategic Finance)

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Requirements:

• Strong sense of ownership, intellectual curiosity, and an ability to think creatively and critically and thrive in a fast-paced, dynamic, and often ambiguous work environment.
• 5+ years of experience with database design, architecture, and modeling techniques in cloud data warehouses (i.e. Snowflake) and data engineering using ETL tools (i.e. DataBricks).
• Expert-level working knowledge of SQL and Python required.
• Experience writing clean, computationally efficient code involving ETL processes and data manipulation via SQL and Python.
• Experience using standard Python analysis packages (e.g., SciPy, NumPy, Pandas).
• Comfort with production level IDEs (e.g., PyCharm, Visual Studio), interactive IDEs (e.g., Databricks, Jupyter), and Version Control (e.g., git, specifically GitHub).
• Experience with dbt or similar data transformation tools, Looker or similar BI tools, Agile methodologies, Finance and accounting data and processes, Anaplan or similar EPM tools, and Excel modeling.

Responsibilities:

• Design and deliver relational and non-relational database models, data pipelines, reporting and visualization solutions by supporting all phases of the analytics development life cycle (ADLC), including requirements gathering, design, development, testing and deployment.
• Recognize and adopt best practices in data warehousing, reporting, and analysis: data integrity, test design, analysis, validation, and documentation.
• Own and document data pipelines and data lineage.
• Identify and troubleshoot data-related and reporting production issues.
• Identify and drive reporting automation, improvement opportunities and new capabilities/tools.
• Be on the lookout for technology best practices and advocate for them.
• Help finance analysts build highly complex queries; be a data access optimization guru.
• Be an advocate for data governance, security, privacy, quality and retention.