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We are seeking a skilled React.js Frontend Developer to join our development team. The ideal candidate will be responsible for building responsive web applications, integrating APIs, and collaborating with designers and backend developers to deliver high-quality user experiences.
Develop and maintain user-facing features using React.js.
Build reusable components and frontend libraries for future use.
Integrate RESTful APIs and third-party services.
Optimize applications for maximum speed and scalability.
Collaborate with UI/UX designers to implement responsive designs.
Write clean, maintainable, and well-documented code.
Troubleshoot and debug application issues.
Participate in code reviews and team discussions.
Ensure cross-browser compatibility and mobile responsiveness.
Strong proficiency in JavaScript (ES6+).
Experience with React.js and React Hooks.
Knowledge of HTML5, CSS3, and responsive design principles.
Experience with API integration using Axios or Fetch.
Familiarity with state management libraries such as Redux or Context API.
Understanding of Git version control.
Basic knowledge of Node.js and REST APIs.
Experience with TypeScript.
Familiarity with Vite, Next.js, or modern frontend build tools.
Knowledge of Material UI, Tailwind CSS, or Bootstrap.
Experience working in Agile/Scrum environments.
Understanding of authentication mechanisms such as JWT and OAuth.
Bachelor's degree in Computer Science, Information Technology, or related field.
1–3 years of experience in frontend web development.
Freshers with strong React.js project experience are encouraged to apply.
Competitive salary package.
Flexible work environment.
Professional development opportunities.
Health insurance and paid leave.
Collaborative and innovative team culture.
A Plant Helper assists in the smooth functioning of plant operations by supporting machine operators and maintenance staff. They are responsible for handling materials, cleaning work areas, loading and unloading goods, and ensuring tools and equipment are available as needed.
They follow safety guidelines, help in basic machine operations, and perform routine tasks to maintain efficiency in the plant. The role requires physical stamina, teamwork, and attention to safety standards.
Overall, a Plant Helper plays an important role in supporting daily operations and maintaining a safe, clean, and productive work environment.
We are seeking an analytical, curious, and detail-oriented Data Analyst to join our Business Intelligence and Analytics team. In this role, you will be responsible for extracting data from various relational databases, performing data hygiene, identifying structural trends, and translating raw numbers into compelling visual dashboards. You will work cross-functionally with product, marketing, and operational teams to help our organization move from intuitive decisions to data-proven strategies.
Write and optimize complex queries to pull data across multiple large relational databases and cloud data warehouses (e.g., Snowflake, BigQuery, AWS Redshift).
Perform table joins, aggregations, and subqueries to combine disconnected metrics into a single, cohesive dataset.
Identify, diagnose, and clean data anomalies, missing values, duplicates, or formatting inconsistencies before analysis.
Document data cleaning pipelines to ensure that recurring data ingestion processes remain reproducible.
Design, deploy, and maintain interactive business intelligence dashboards utilizing enterprise visual tools (Power BI, Tableau, or Looker).
Consistently track and monitor core company KPIs (Key Performance Indicators) such as customer acquisition costs, monthly active users, or operational conversion rates.
Apply basic statistical techniques (such as mean, median, correlation, and variance analysis) to uncover operational trends and identify seasonal performance shifts.
Conduct deep-dive root cause analyses when a standard operational metric drops or shifts unexpectedly.
Translate intricate data structures into plain language and short summary summaries for non-technical managers.
Collaborate with data engineers to improve underlying pipeline infrastructure and define data schema requirements.
Database Management: Proficiency in SQL (Joins, CTEs, Window functions, Group By).
Business Intelligence: Hands-on experience building multi-page dashboards in Power BI, Tableau, or equivalent.
Data Manipulation: High competency in advanced Excel (Pivot tables, Power Query, advanced statistical formulas).
Scripting (Nice-to-Have / Growing Trend): Foundational knowledge of Python or R (specifically packages like Pandas, NumPy, and Matplotlib) for automated reporting.
Critical Thinking: The ability to challenge a vague business query ("Why are sales slow?") and transform it into a series of highly specific data-driven hypotheses.
Data Governance Focus: Extreme attention to detail to ensure data privacy frameworks (like keeping Personally Identifiable Information — PII hidden) are respected.
Agility & Continuous Learning: Adaptability to rapidly picking up new SaaS reporting stacks, enterprise toolkits, and dynamic visualization tools.
Typical Data Analyst Day-to-Day WorkflowMorning: Triage inbound analytical request tickets or verify dashboard refresh health logs. Midday: Extract datasets via SQL, perform diagnostic filtering, and build calculated measures. Afternoon: Wireframe visual charts, meet with business leads to scope out requirements, and present recent performance findings.
Morning: Triage inbound analytical request tickets or verify dashboard refresh health logs.
Midday: Extract datasets via SQL, perform diagnostic filtering, and build calculated measures.
Afternoon: Wireframe visual charts, meet with business leads to scope out requirements, and present recent performance findings.