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)