Engineer - Data Analyst

Role and Responsibility

• Build Dashboards & Reports: Design, develop, and maintain interactive dashboards and reports in Tableau and/or Power BI that deliver actionable insights to business stakeholders. Own the full lifecycle from requirements gathering to published, production-grade visualizations.
• Data Analysis & Storytelling: Analyze manufacturing, operational, and financial data to identify trends, anomalies, and opportunities. Translate findings into clear, compelling visual narratives that drive decision-making across teams.
• SQL & Data Exploration: Write SQL queries in Snowflake to extract, transform, and validate data for reporting. Perform ad-hoc analyses to answer business questions and support strategic initiatives.
• Support Data Modeling: Collaborate with data engineers to define reporting requirements and contribute to dbt model development - building or modifying staging and mart models that feed dashboards and reports.
• Analytical Mindset: Strong attention to detail with the ability to spot data inconsistencies, ask the right questions, and deliver accurate, trustworthy reporting.
• Documentation & Training: Document data definitions, metric calculations, and dashboard usage guides. Provide training and support to business users to promote self-service analytics adoption.

Expectation from the Candidate

• Experience: 2+ years of experience in a data analyst, BI analyst, or reporting analyst role with a portfolio of dashboards and reports delivered to business stakeholders.
• Technical Prowess: o Strong proficiency in Tableau and/or Power BI: calculated fields, LOD expressions (Tableau), DAX measures (Power BI), parameters, dynamic filters, row-level security, and performance optimization.
• Working knowledge of SQL for querying Snowflake: JOINs, CTEs, window functions, aggregations, and basic data transformation.
• Foundational understanding of dbt: ability to read and modify existing models, understand the staging/mart layer structure, and run dbt commands for testing and documentation.
• Familiarity with data modeling concepts: star schemas, fact/dimension tables, and how they translate into efficient dashboard data sources.
• Basic Python skills for data wrangling, automation, or extending analytics workflows (pandas, notebooks).
• Must have skills: Power BI (Strong), Tableau (Strong)
• Good to have skills: Data Modeling (Capable), Python (Capable), SQL (Capable)