Data Analyst
7 days ago
Key Responsibilities
- Collect, clean, and validate data from multiple sources (databases, APIs, spreadsheets, IoT sensors, remote sensing, etc.).
- Conduct exploratory and advanced data analysis to identify trends, patterns, and anomalies, including agriculture and farm-related datasets (crop yield, soil, weather, and satellite imagery).
- Develop dashboards and reports using tools like Power BI, Tableau, or Superset.
- Design of data analytics dashboards and wireframe design in Figma.
- Work closely with client and business teams to define KPIs, track performance, and generate insights, with emphasis on agriculture projects.
- Write and optimize SQL queries for data extraction and transformation.
- Work closely with other database team members to ensure data quality, consistency, and automation.
- Present findings to stakeholders using clear visualizations and storytelling.
- Support predictive and statistical modelling projects (basic ML/forecasting exposure preferred), including agriculture-focused forecasting (yield prediction, demand estimation, climate impact analysis).
Required Skills & Qualifications
- Bachelors degree in Computer Science, Statistics, Mathematics, Economics, Agriculture, or related field.
- 3+ years of experience as a Data Analyst or in a similar role.
- Experience with PostgreSQL database.
- Hands-on experience with BI tools (Tableau, Power BI, Superset, or similar).
- Experience with Data Analytics Platform Design and Figma.
- Strong proficiency in SQL (writing complex queries, joins, aggregations).
- Proficiency in Excel (advanced formulas, pivot tables, macros).
- Good knowledge of Python or R for data manipulation and analysis.
- Strong analytical thinking and problem-solving skills.
- Experience with statistical concepts (correlation, regression, hypothesis testing).
- Excellent communication skills for conveying technical insights to non-technical stakeholders.
- Exposure to agri analytics, GIS, or environmental datasets will be an added advantage.
Preferred Skills
- Experience with big data tools.
- Knowledge of ETL pipelines and data warehousing concepts.
- Exposure to cloud platforms (AWS, Azure, GCP).
- Basic knowledge of machine learning or predictive modelling.
- Familiarity with agri-tech use cases such as farm management systems, carbon credits, or supply chain traceability.
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