Job Summary :

We are looking for a skilled Data Application Developer with a strong foundation in R (preferred) or Python to build and enhance data-driven tools and internal applications. The ideal candidate has hands-on experience with R Shiny or Python-based web frameworks, strong SQL expertise, and the ability to work with large datasets to deliver scalable, high-performance solutions.

Key Responsibilities :

- Design, develop, and maintain data applications using R (Shiny preferred) or Python frameworks.

- Build interactive dashboards and custom user inputs with a focus on performance and usability.

- Implement non-blocking / asynchronous user operations in Shiny or equivalent frameworks.

- Develop and maintain data pipelines for ingestion, transformation, and storage of structured and unstructured data.

- Use Git for version control, code reviews, and collaborative development workflows.

- Develop efficient data manipulation workflows using packages such as dplyr, data.table, pandas, NumPy, etc.

- Write optimized SQL queries and work with large-scale relational databases.

- Handle and process large datasets efficiently and reliably.

- Collaborate with product and business teams to translate requirements into technical solutions.

- Assist in integrating LLM/AI capabilities into data tools and internal applications.

- (Optional) Build reports or integrations using Power BI or similar BI tools.

- Ensure high code quality, documentation, testing, and maintainability.

Required Skills & Qualifications :

- 2 to 3 years of professional experience in data application development, analytics engineering, or a similar role.

- Strong proficiency in R or Python (R is highly preferred).

- Hands-on experience with R / Python Shiny or equivalent Python frameworks (e.g., Streamlit, Dash, FastAPI).

- Solid understanding of data manipulation libraries/packages.

- Strong knowledge of SQL and experience working with complex queries.

- Expertise in writing complex SQL queries, including multi-table JOINs, window functions, CTEs (including recursive), and subqueries (correlated and non-correlated).

- Strong experience in SQL performance optimization and large-scale data handling, including use of indexes, execution plans, and working with partitioned tables and high-volume datasets.

- Strong understanding of statistics, including practical experience with :

- Descriptive statistics (mean, median, variance, standard deviation, percentiles)

- Probability distributions (normal, binomial, Poisson)

- Hypothesis testing (t-tests, chi-square tests, ANOVA)

- Confidence intervals and statistical significance

- Correlation and basic regression analysis

- Interpreting statistical results for business decision-making

- Proven experience working with large datasets.

- Good understanding of event-driven / non-blocking application design.

- Experience building custom UI components and user inputs in Shiny or similar frameworks.

- Strong working knowledge of Git (branching strategies, pull requests, code reviews).

- Experience designing and maintaining data pipelines (ETL/ELT workflows).

- Basic working knowledge of LLMs / AI integration, such as using APIs (OpenAI, HuggingFace, etc.), prompt design, or embedding AI features into applications.

Preferred / Nice to Have :

- Experience with Power BI or other BI tools.

- Familiarity with cloud platforms (AWS/GCP/Azure), APIs, CI/CD, or containerization (Docker).

About Company :

Hi there! We are Auriga IT.

We power businesses across the globe through digital experiences, data and insights. From the apps we design to the platforms we engineer, we're driven by an ambition to create world-class digital solutions and make an impact. Our team has been part of building the solutions for the likes of Zomato, Yes Bank, Tata Motors, Amazon, Snapdeal, Ola, Practo, Vodafone, Meesho, Volkswagen, Droom, ICICI and many more.

We are a group of people who just could not leave our college-life behind and the inception of Auriga was solely based on a desire to keep working together with friends and enjoying the extended college life.