11+ BREW Jobs in India

• Strong experienced Product Design Profile
• Mandatory (Experience 1) – Must have 8+ YOE in Product Design, with a focus on B2C or B2B2C Products
• Mandatory (Experience 2) – Must have strong experience in Project Management - Using Jira and other similar tools to manage projects efficiently
• Mandatory (Designation) – Must be Manager / Staff or above designation in Current role
• Mandatory (Team Managememt) - Must have atleast recent 2+ YOE as a Team Manager (Not mentoring, should be in a complete Manager role)
• Mandatory (Portfolio) - Must have strong High-fidelity UI Designs, Interaction models, and Design systems for Large-scale B2C Products
• Mandatory (Company) - Large-Scale B2C Products
• Mandatory (Gender) - Male candidates only

Preferred

• Preferred (Experience) - Retail domain experience

Responsibilities:

Use quantitative methods such as business simulations, data mining, modeling, and advanced statistical techniques to solve problems. The Data Scientist contributes by serving as a technical lead for analytics initiatives of low‑to‑medium complexity or business impact and supporting high‑profile, enterprise initiatives such as the Engineered Value Chain. 

In this role, you will act as an individual contributor on analytic teams, partnering on cross‑functional projects, and guiding technical delivery. You will also mentor procurement professionals on the technical approaches used to solve problems presented by business units, service organizations, dealers, or customers. 

Job duties/Responsibilities include but not limited to:

• Lead and deliver analytics initiatives by defining analytical approaches, building models, and translating insights into business actions for procurement and enterprise stakeholders. 
• Develop, train, validate, and monitor predictive models using a broad set of machine learning/statistical methods to support targeted business outcomes. 
• Design and implement ETL/data pipelines and integrate data sources to create safe, trusted datasets for reporting and analytics (including Snowflake and SQL-based workflows). 
• Build executive-ready dashboards and decision tools (e.g., Power BI) that enable data‑driven leadership decisions. 
• Apply data modelling best practices (conceptual, logical, physical models) and support integration/transformation patterns to analytics environments and warehouses. 
• Partner cross‑functionally (Procurement, Digital/IT, Finance, operations stakeholders) to deploy analytics solutions into production and ensure adoption. 
• Operate with strong data governance and operational rigor, including troubleshooting data issues, managing access/user needs, and supporting reliable analytics operations. 
• Use modern engineering practices (e.g., GitLab/DevOps toolchains) to improve repeatability, scalability, and maintainability of analytics solutions. 

Must Have Skills

• Strong AI/ML background across model development and validation, including methods such as time series, clustering, tree-based algorithms, generalized linear models, or neural networks.                           
• Strong SQL + Snowflake proficiency for ETL, transformation, and analytics-ready datasets. 
• Experience with cloud solutions, solution integration, IT operations, and data governance. 
• Proficiency in Python programming language.
• Proficiency in Prompt Engineering.
• Experience with front-end technologies such as HTML, CSS, and JavaScript.
• Experience with back-end technologies such as Django, Flask, or Node.js.
• Solid grasp of database technologies such as MySQL, PostgreSQL, or MongoDB.
• Creation of CI,CD Pipelines for ML algorithms, training, prediction pipelines
• Proficiency in Machine Learning Operations.
• Work with business, data scientists to ensure value realization, ROI on operationalization of models
• Strong understanding of statistical analysis and machine learning algorithms.
• Containerization, packaging of ML models
• Experience with data visualization tools such as Power BI.
• Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity.
• Experience with Large Language Models (LLMs) and Natural Language Processing (NLP) technologies.

Good To Have Skills:

• Experience with cloud-first and agile methodologies.
• Strong understanding of statistical analysis and machine learning algorithms.
• Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity.

Required Skill:

• Degree in Computer Science, Business, Mathematics, Economics, Statistics, Engineering, or related field.  

Key Skills Required:

• Strong hands-on experience with Terraform
• Proficiency in CI/CD tools (e.g., Jenkins, GitLab CI, Azure DevOps, etc.)
• Experience working on Azure or GCP cloud platforms (at least one is mandatory)
• Good understanding of DevOps practices

Job Summary:

We are looking for a motivated and detail-oriented Data Engineer with 1–2 years of experience to join our data engineering team. The ideal candidate should have solid foundational skills in SQL and Python, along with exposure to building or maintaining data pipelines. You’ll play a key role in helping to ingest, process, and transform data to support various business and analytical needs.

Key Responsibilities:

• Assist in the design, development, and maintenance of scalable and efficient data pipelines.
• Write clean, maintainable, and performance-optimized SQL queries.
• Develop data transformation scripts and automation using Python.
• Support data ingestion processes from various internal and external sources.
• Monitor data pipeline performance and help troubleshoot issues.
• Collaborate with data analysts, data scientists, and other engineers to ensure data quality and consistency.
• Work with cloud-based data solutions and tools (e.g., AWS, Azure, GCP – as applicable).
• Document technical processes and pipeline architecture.

Core Skills Required:

• Proficiency in SQL (data querying, joins, aggregations, performance tuning).
• Experience with Python, especially in the context of data manipulation (e.g., pandas, NumPy).
• Exposure to ETL/ELT pipelines and data workflow orchestration tools (e.g., Airflow, Prefect, Luigi – preferred).
• Understanding of relational databases and data warehouse concepts.
• Familiarity with version control systems like Git.

Preferred Qualifications:

• Experience with cloud data services (AWS S3, Redshift, Azure Data Lake, etc.)
• Familiarity with data modeling and data integration concepts.
• Basic knowledge of CI/CD practices for data pipelines.
• Bachelor’s degree in Computer Science, Engineering, or related field.

Requirements:

· Identifying opportunities in target markets for your organization’s products and services.

· Generating leads through cold calling prospective clients or networking at trade shows.

· Developing and nurturing relationships with key customer accounts

· Keeping up with the latest industry developments, including market positioning of corporate competitors.

Responsibilities:

• Contacting potential clients to establish rapport and arrange meetings.
• Planning and overseeing new marketing initiatives.
• Researching organizations and individuals to find new opportunities.
• Increasing the value of current customers while attracting new ones.
• Finding and developing new markets and improving sales.