Candidatul Ideal
This role is focused on structured data management, not dashboards. You will own the databases that power both platforms: a product classification system with hundreds of entries and industry-standard mappings, data processing pipelines that ingest and validate environmental data at scale, and an emission factor database aligned with international reporting standards. You will also work with AI models to extract structured information from technical documents. If you are fascinated by database design, data pipelines, and turning messy real-world data into clean, queryable structures, this role is for you.
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Key Responsibilities
- Extract, clean, and analyze complex, medium-to-large scale datasets from diverse internal and external sources to uncover actionable trends and insights.
- Design, build, and maintain interactive dashboards, automated reports, and data visualizations that monitor key performance indicators (KPIs).
- Conduct in-depth exploration data analysis (EDA) and quantitative research to support strategic decision-making, product direction, and business initiatives.
- Translate complex statistical findings into clear, compelling narratives and recommendations for both technical and cross-functional stakeholders.
- Proven professional experience as a Data Analyst, with a strong track record of independently researching and analyzing medium-to-large datasets.
- Data Querying: Advanced proficiency in SQL for complex querying, data aggregation, and transformation across relational databases.
- Programming for Analysis: Strong hands-on experience with Python (specifically libraries like Pandas, NumPy, Matplotlib/Seaborn) or R for statistical computing, data wrangling, and automating analytical workflows.
- Statistical Rigor: Solid foundation in applied statistics, hypothesis testing (e.g., A/B testing methodologies), and quantitative research techniques.
- Experience querying and working within cloud data warehouses (e.g., Snowflake, Google BigQuery, AWS Redshift) and utilizing data transformation tools like dbt.
- Big Data Ecosystem: Familiarity with distributed computing frameworks (e.g., Apache Spark) for handling exceptionally large datasets.
- Advanced Analytics: A foundational understanding of predictive modeling, forecasting, or applied machine learning concepts.
- Data Visualization: Deep expertise in building insightful and optimized dashboards using industry-standard BI tools & Spreadsheets.
- Tools: Modern development environment with AI-assisted tooling.
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CarbonTool is a corporate sustainability reporting platform. We help organisations calculate their carbon footprint across all GHG Protocol scopes, set science-based targets, and produce CSRD-compliant sustainability reports — powered by a comprehensive emission factor database and automated data processing.
Both platforms share a single engineering team and backend infrastructure. You will work on software that directly contributes to decarbonising the built environment — a sector responsible for nearly 40% of global carbon emissions.
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