Business Analytics Engineer (Python | SQL | AI-Assisted Development)

Overview

This role is focused on building and scaling a business analytics capability using Python and SQL, with an emphasis on rapid execution, exploratory analysis, and AI-assisted development workflows. The position is well suited for an engineer who is comfortable working independently, moving fast, and leveraging modern AI tools to accelerate coding, analysis, and problem-solving.

The role requires a strong analytical mindset, hands-on data engineering and querying skills, and the ability to translate raw business data into actionable insights. The ideal candidate is pragmatic, adaptable, and comfortable working in a dynamic environment, including availability across weekdays and weekends as needed.

Job Description

  • Develop and maintain Python-based analytics workflows for business reporting and insights

  • Write efficient and reliable SQL queries to extract, transform, and analyze data from relational data sources

  • Build exploratory analyses, dashboards, and ad-hoc reports to support business decision-making

  • Leverage AI-assisted coding tools (e.g., Copilot-style workflows) to speed up development, iteration, and debugging

  • Collaborate closely with stakeholders to understand data needs and translate them into analytical solutions

  • Ensure data accuracy, consistency, and reliability across analytics outputs

  • Operate with a high degree of ownership and responsiveness in a fast-moving environment

Skills & Requirements

  • Strong hands-on experience with Python for data analysis and scripting

  • Solid proficiency in SQL, including complex queries, joins, aggregations, and performance considerations

  • Experience working on business analytics, reporting, or data-driven problem solving

  • Comfort working independently with minimal hand-holding

  • Familiarity with AI-based development approaches and tooling for faster coding and analysis

  • Ability to manage workload across 5 days per week, including weekends


    Nice to Have:

  • Experience with analytics libraries such as Pandas, NumPy, or similar

  • Exposure to BI tools or lightweight dashboards

  • Experience supporting early-stage or fast-growing products

  • Background in data engineering, analytics engineering, or hybrid analyst-engineer roles


    Summary of Skill-set:

    Business Analytics, Python, SQL, Data Analysis, AI-Assisted Coding, Rapid Prototyping, Independent Execution, Problem Solving

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