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

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.

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.

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.

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.

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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