Associate Data & Analytics Engineer

Key Responsibilities

• Data Engineering: Support the design, development, and maintenance of data pipelines and integrations (e.g., using Databricks, SQL, or Python).
• Transform Data: Transform raw data into clean, analytics-ready datasets following best practices for quality and performance.
• Identify & Resolve Issues: Identify, investigate, and resolve data anomalies or quality issues in coordination with business and engineering teams.
• Analytics & Reporting: Conduct exploratory analyses and create ad hoc or manual reports to support business questions and urgent needs.
• Documentation: Maintain consistent documentation of data definitions, logic, and reporting standards.
• Visualization: Build and maintain interactive dashboards and visualizations in Power BI, Databricks Dashboards, or custom Data Apps.
• Collaboration: Collaborate with stakeholders to define KPIs and ensure visualizations align with business goals.
• Support Applications: Support the rollout and improvement of data applications that make analytics more accessible across the organization.
• AI Exploration: Participate in exploratory projects using AI, ML, or LLM tools to enhance data workflows and automate insights.
• Development & Evaluation: Assist with the development and evaluation of predictive models under senior guidance.
• Research Tools: Research emerging tools and methods that can improve analytics efficiency and scalability.

Qualifications

• Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, or a related field.
• 1–3 years of professional or academic experience in analytics, data engineering, or data visualization.
• Proficiency in SQL and basic familiarity with Python or PySpark.
• Hands-on experience with Power BI, Databricks, or similar BI and data platforms.
• Strong analytical and troubleshooting skills, with attention to detail and data accuracy.
• Ability to communicate findings clearly to both technical and non-technical audiences.