CoffeeBeans

Role Overview

We're looking for experienced Data Engineers who can independently design, build, and manage scalable data platforms. You'll work directly with clients and internal teams to develop robust data pipelines that support analytics, AI/ML, and operational systems.

You’ll also play a mentorship role and help establish strong engineering practices across our data projects.

Key Responsibilities

• Design and develop large-scale, distributed data pipelines (batch and streaming)
• Implement scalable data models, warehouses/lakehouses, and data lakes
• Translate business requirements into technical data solutions
• Optimize data pipelines for performance and reliability
• Ensure code is clean, modular, tested, and documented
• Contribute to architecture, tooling decisions, and platform setup
• Review code/design and mentor junior engineers

Must-Have Skills

• Strong programming skills in Python and advanced SQL
• Solid grasp of ETL/ELT, data modeling (OLTP & OLAP), and stream processing
• Hands-on experience with frameworks like Apache Spark, Flink, etc.
• Experience with orchestration tools like Airflow
• Familiarity with CI/CD pipelines and Git
• Ability to debug and scale data pipelines in production

Preferred Skills

• Experience with cloud platforms (AWS preferred, GCP or Azure also fine)
• Exposure to Databricks, dbt, or similar tools
• Understanding of data governance, quality frameworks, and observability
• Certifications (e.g., AWS Data Analytics, Solutions Architect, Databricks) are a bonus

What We’re Looking For

• Problem-solver with strong analytical skills and attention to detail
• Fast learner who can adapt across tools, tech stacks, and domains
• Comfortable working in fast-paced, client-facing environments
• Willingness to travel within India when required

As an L3 Data Scientist, you’ll work alongside experienced engineers and data scientists to solve real-world problems using machine learning (ML) and generative AI (GenAI). Beyond classical data science tasks, you’ll contribute to building and fine-tuning large language model (LLM)– based applications, such as chatbots, copilots, and automation workflows.

Key Responsibilities

• Collaborate with business stakeholders to translate problem statements into data science tasks.
• Perform data collection, cleaning, feature engineering, and exploratory data analysis (EDA).
• Build and evaluate ML models using Python and libraries such as scikit-learn and XGBoost.
• Support the development of LLM-powered workflows like RAG (Retrieval-Augmented Generation), prompt engineering, and fine-tuning for use cases including summarization, Q&A, and task automation.
• Contribute to GenAI application development using frameworks like LangChain, OpenAI APIs, or similar ecosystems.
• Work with engineers to integrate models into applications, build/test APIs, and monitor performance post-deployment.
• Maintain reproducible notebooks, pipelines, and documentation for ML and LLM experiments.
• Stay updated on advancements in ML, NLP, and GenAI, and share insights with the team.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
• 6–9 years of experience in data science, ML, or AI (projects and internships included).
• Proficiency in Python with experience in libraries like pandas, NumPy, scikit-learn, and matplotlib.
• Basic exposure to LLMs (e.g., OpenAI, Cohere, Mistral, Hugging Face) or a strong interest with the ability to learn quickly.
• Familiarity with SQL and structured data handling.
• Understanding of NLP fundamentals and vector-based retrieval techniques (a plus).
• Strong communication, problem-solving skills, and a proactive attitude.

Nice-to-Have (Not Mandatory)

• Experience with GenAI prototyping using LangChain, LlamaIndex, or similar frameworks.
• Knowledge of REST APIs and model integration into backend systems.
• Familiarity with cloud platforms (AWS/GCP/Azure), Docker, or Git.

As an L1/L2 Data Scientist, you’ll work alongside experienced engineers and data scientists to solve real-world problems using machine learning (ML) and generative AI (GenAI). Beyond classical data science tasks, you’ll contribute to building and fine-tuning large language model (LLM)– based applications, such as chatbots, copilots, and automation workflows.

Key Responsibilities

• Collaborate with business stakeholders to translate problem statements into data science tasks.
• Perform data collection, cleaning, feature engineering, and exploratory data analysis (EDA).
• Build and evaluate ML models using Python and libraries such as scikit-learn and XGBoost.
• Support the development of LLM-powered workflows like RAG (Retrieval-Augmented Generation), prompt engineering, and fine-tuning for use cases including summarization, Q&A, and task automation.
• Contribute to GenAI application development using frameworks like LangChain, OpenAI APIs, or similar ecosystems.
• Work with engineers to integrate models into applications, build/test APIs, and monitor performance post-deployment.
• Maintain reproducible notebooks, pipelines, and documentation for ML and LLM experiments.
• Stay updated on advancements in ML, NLP, and GenAI, and share insights with the team.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
• 2.5–5 years of experience in data science, ML, or AI (projects and internships included).
• Proficiency in Python with experience in libraries like pandas, NumPy, scikit-learn, and matplotlib.
• Basic exposure to LLMs (e.g., OpenAI, Cohere, Mistral, Hugging Face) or strong interest with the ability to learn quickly.
• Familiarity with SQL and structured data handling.
• Understanding of NLP fundamentals and vector-based retrieval techniques (a plus).
• Strong communication, problem-solving skills, and a proactive attitude.

Nice-to-Have (Not Mandatory)

• Experience with GenAI prototyping using LangChain, LlamaIndex, or similar frameworks.
• Knowledge of REST APIs and model integration into backend systems.
• Familiarity with cloud platforms (AWS/GCP/Azure), Docker, or Git.

We are looking for experienced Data Engineers who can independently build, optimize, and manage scalable data pipelines and platforms.

In this role, you’ll:

• Work closely with clients and internal teams to deliver robust data solutions powering analytics, AI/ML, and operational systems.
• Mentor junior engineers and bring engineering discipline into our data engagements.

Key Responsibilities

• Design, build, and optimize large-scale, distributed data pipelines for both batch and streaming use cases.
• Implement scalable data models, warehouses/lakehouses, and data lakes to support analytics and decision-making.
• Collaborate with stakeholders to translate business requirements into technical solutions.
• Drive performance tuning, monitoring, and reliability of data pipelines.
• Write clean, modular, production-ready code with proper documentation and testing.
• Contribute to architectural discussions, tool evaluations, and platform setup.
• Mentor junior engineers and participate in code/design reviews.

Must-Have Skills

• Strong programming skills in Python and advanced SQL expertise.
• Deep understanding of ETL/ELT, data modeling (OLTP & OLAP), warehousing, and stream processing.
• Hands-on with distributed data processing frameworks (Apache Spark, Flink, or similar).
• Experience with orchestration tools like Airflow (or similar).
• Familiarity with CI/CD pipelines and Git.
• Ability to debug, optimize, and scale data pipelines in production.

Good to Have

• Experience with cloud platforms (AWS preferred; GCP/Azure also welcome).
• Exposure to Databricks, dbt, or similar platforms.
• Understanding of data governance, quality frameworks, and observability.
• Certifications (e.g., AWS Data Analytics, Solutions Architect, or Databricks).

Other Expectations

• Comfortable working in fast-paced, client-facing environments.
• Strong analytical and problem-solving skills with attention to detail.
• Ability to adapt across tools, stacks, and business domains.
• Willingness to travel within India for short/medium-term client engagements, as needed.

Job Description - Lead Java Developer

As a Backend Developer, you will play a crucial role in designing and developing the business logic and backend systems for our products. You will work closely with frontend developers to design and develop functional, performant, and complete APIs. You will also work on decrypting existing enterprise software systems and connecting applications to applicable data sources. Additionally, you will write unit, integration, and performance tests, develop automation tools, and continuous integration pipelines for daily tasks. Your work will be of high quality, well-documented, and efficient. You will also challenge ideas and opinions to avoid errors and inefficient solutions.

What are we looking for?

• A bachelor's degree in Computer Science or a related field is a plus, but not mandatory.
• 7+ years of experience as a backend developer with experience in Java, Microservices, SpringBoot, etc.
• Significant API expertise for large-scale apps and performance optimization.
• Deep knowledge of programming and object-oriented engineering (e.g., SOLID, clean architecture).
• Good knowledge of Java.
• Knowledge of distributed systems tech stacks like Kafka, ELK, in-memory databases, Cassandra or other such DB's
• Strong communication skills with the ability to communicate complex technical concepts and align the organization on decisions.
• Strong problem-solving skills to quickly process complex information and present it clearly and effectively.
• Ability to utilize team collaboration to create innovative solutions efficientl