DrinkPrime is hiring for a fresher entry level Data Analyst Trainee in India

Position:

• Data Analyst Trainee (Graduate Engineer Trainee - Data Analysis)

Company:

• DrinkPrime

Location:

• Bengaluru, Karnataka, India

Job type:

• Full-time

Job mode:

• Onsite

Job requisition id:

• Not specified

Years of experience:

• 0-3 years

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Company description

• DrinkPrime is an innovative water solutions company that aims to redefine how people access clean drinking water in India.

• Established with the goal of addressing the inconsistency in water quality across Indian cities, the company has developed a subscription-based water purifier model.

• This model allows households to access safe drinking water without the high upfront costs of purchasing and maintaining a purifier.

• DrinkPrime’s approach is technology-first, using IoT-enabled devices and data-driven monitoring to ensure water quality remains consistent.

• The company has secured funding from prominent venture capital firms and angel investors who believe in its mission to bring affordable water purification to every home.

• Its vision goes beyond simply providing a service — it aims to build a large-scale movement for safe water access, ensuring every family can drink with confidence.

• As part of its growth strategy, DrinkPrime is looking to attract talented professionals who can contribute to its mission and help strengthen its data capabilities.

• Working here means joining a passionate, mission-driven team focused on making a tangible social impact.

• The environment fosters innovation, continuous learning, and cross-functional collaboration.

• With a strong emphasis on problem-solving and customer satisfaction, DrinkPrime positions itself as a brand that is changing both habits and mindsets about water consumption in India.

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Profile overview

• The Graduate Engineer Trainee - Data Analysis role is designed for early-career professionals or recent graduates who are passionate about working with data to create actionable insights.

• The position involves working with various types of data, including operational, customer, and product performance data, to support decision-making processes across the organization.

• You will be gathering data from multiple sources, ensuring its accuracy, and preparing it for analysis in a structured format.

• A key part of your role will be to identify trends, detect anomalies, and generate valuable insights through exploratory and statistical analyses.

• You will be expected to work closely with different business teams, including business analysts, engineers, and product managers, to understand requirements and deliver data solutions.

• The role includes creating clear visualizations and dashboards to present findings in a way that is easy to understand for both technical and non-technical stakeholders.

• There will be opportunities to experiment with different tools and techniques in data analytics, allowing you to expand your technical skills while contributing to real-world business problems.

• As a trainee, you will be provided with guidance and mentorship, but you are also expected to take initiative, learn independently, and stay updated with the latest trends in analytics.

• Success in this role comes from combining technical proficiency with strong communication skills, enabling you to convey complex insights in a simple and actionable manner.

• The position offers a platform to grow within the company and build a career in data analytics, while directly contributing to the larger mission of improving access to safe drinking water.

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Qualifications

• Educational background in engineering, computer science, statistics, mathematics, or a related field is preferred.

• Familiarity with data analysis concepts and techniques, including exploratory data analysis, statistical modeling, and data visualization.

• Knowledge of common analytics tools such as Excel, SQL, Power BI, or Tableau.

• Basic programming skills in Python or R will be considered an advantage.

• Strong logical thinking and problem-solving abilities.

• Good understanding of how to clean, validate, and prepare datasets for analysis.

• Ability to identify trends and patterns in large volumes of data.

• Strong communication skills to explain data findings to non-technical audiences.

• Willingness to learn new tools, techniques, and frameworks for analytics.

• Self-motivated with an eagerness to contribute to a mission-driven organization.

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Additional info

• This is a full-time, onsite role based in Bengaluru, Karnataka, India.

• The position is targeted at fresh graduates or those with up to three years of experience.

• You will have the opportunity to work with experienced data professionals and business leaders in a collaborative environment.

• The company values curiosity, teamwork, and a commitment to delivering results that align with its mission.

• Your work will directly support strategic decisions, operational improvements, and customer satisfaction efforts.

• You will gain exposure to multiple areas of the business, providing a strong foundation for a career in analytics.

• The role involves continuous learning and adapting to new technologies and industry practices.

• This is an ideal position for someone who wants to combine technical skills with meaningful social impact.

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Detailed Paraphrased Job Responsibilities

Data Gathering and Preparation

• Collect data from a variety of internal systems such as CRM platforms, operational dashboards, IoT devices, and external sources including market research and public datasets.

• Ensure the collection process is systematic, well-documented, and aligned with business needs.

• Verify that all sources of data are reliable and relevant to ongoing projects.

Data Cleaning and Validation

• Inspect datasets for errors, inconsistencies, and missing values before analysis.

• Use appropriate techniques to handle null values, duplicates, and formatting issues.

• Ensure that cleaned data meets the company’s accuracy and completeness standards.

Data Structuring

• Transform raw datasets into organized formats suitable for analysis, such as structured tables or well-labeled spreadsheets.

• Apply data normalization and standardization techniques to ensure uniformity across sources.

• Create clear metadata and documentation for future reference.

Exploratory Data Analysis (EDA)

• Analyze datasets to detect underlying trends, relationships, and anomalies.

• Use summary statistics, correlation analysis, and visual inspection to understand the nature of the data.

• Formulate hypotheses for further testing based on initial observations.

Statistical Analysis and Data Mining

• Apply statistical techniques such as regression, hypothesis testing, and clustering.

• Use data mining methods to discover patterns that might not be immediately visible.

• Generate meaningful metrics that can guide business decisions.

Reporting and Dashboard Development

• Create reports that summarize findings in a concise and actionable format.

• Develop interactive dashboards using tools like Power BI, Tableau, or Excel to allow stakeholders to explore data in real-time.

• Update reports and dashboards regularly to reflect the most recent data.

Data Visualization

• Use appropriate chart types, graphs, and infographics to present data findings.

• Ensure visualizations are intuitive, easy to interpret, and tailored to the audience.

• Follow best practices in design to avoid misrepresentation of data.

Presentation of Insights

• Communicate findings to internal teams through presentations, documents, and visual dashboards.

• Highlight actionable recommendations supported by data evidence.

• Adapt the level of detail based on whether the audience is technical or non-technical.

Data Pipeline Support

• Assist in the development of basic data pipelines to automate recurring data tasks.

• Monitor pipelines for errors and ensure timely delivery of processed data.

• Collaborate with engineers to improve efficiency and reliability.

Collaboration with Cross-functional Teams

• Work alongside business analysts to understand business problems and translate them into analytical tasks.

• Collaborate with data engineers to ensure infrastructure supports analytics requirements.

• Engage with software teams to integrate analytics into product features.

Business Requirement Translation

• Interpret business questions and objectives into measurable analytics goals.

• Define the scope, methodology, and success criteria for analytics projects.

• Provide regular updates to stakeholders on progress and results.

Continuous Learning

• Stay updated with new analytics tools, software updates, and emerging technologies in data science.

• Participate in training sessions, workshops, and knowledge-sharing forums.

• Experiment with advanced analytics techniques to expand your skillset.

Industry Awareness

• Keep track of industry trends, market shifts, and competitor strategies.

• Identify opportunities where data analytics can provide a competitive advantage.

• Share relevant insights with leadership to support strategic decisions.

Documentation

• Maintain detailed documentation for datasets, analytical processes, and methodologies.

• Ensure documentation is accessible for future reference and auditing purposes.

• Standardize documentation formats across the team.

Reproducibility and Transparency

• Follow best practices in version control and data management.

• Ensure analytical workflows can be replicated by others.

• Maintain transparency in methodologies and assumptions.

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Please click here to apply.