Big Data Engineer

Kindly note that candidates who have graduated in 2022 and 2023 only will be considered for the role who are based in Mumbai, immediate joiners

JD - Data Operations Analyst

What is the job and team like

• As a Data Operations Analyst we manage business reporting of numerous teams, constantly monitor performance
• Checking the integrity of the revenue reporting done by the different systems for the correct profitability to be
• reported to the CXOs
• Send reports periodically and alert stakeholders for changes in the key performance metrics
• Allocate efforts to different Business Implementations that help build Profit/Loss statement for the Financials.
• Track crucial data points which affect the core of the business and escalate it to senior stakeholders

Roles and Responsibilities

• Graduate in IT Background(BE/BSc IT/ BCA) 2022 and 2023 graduates only
• Executing a set of business processes daily/weekly/monthly as per Business requirement.
• Provide ad-hoc data support on any urgent reports and material in an expedited manner
• Maintain a list of open tasks and escalations, and send updates to the relevant stakeholders
• Have an eye for detail, should have the ability to look at numbers, spot trends and identify gaps
• Identify efficient and meaningful ways to communicate data and analysis through ongoing reports and dashboards
• Proficiency in SQL, Excel and any statistical and analytical tools such as SAS, SPSS is a big plus
• Managing master data, including creation, updates, and deletion.
• Ability to work in a fast paced, technical, cross functional environment
• Familiarity with Internet Industry and Online Advertising Business is a plus

Ideal candidate

• Import and export large volume of data to database tables as required
• Should be able to write Data Definition Language or Data Manipulation Language SQL commands
• Develop programs, methodologies to get analyzable data on a regular basis
• Good team player and multi-tasker
• Should have the ability to learn and adapt to change
• Self-starter Must be productive with minimal direction
• High-level written and verbal communication sk

Job Details

Work mode- In office

Must have skills - SQL, MS Excel, Communications

Graas uses predictive AI to turbo-charge growth for eCommerce businesses. We are “Growth-as-a-Service”. Graas is a technology solution provider using predictive AI to turbo-charge growth for eCommerce businesses. Graas integrates traditional data silos and applies a machine-learning AI engine, acting as an in-house data scientist to predict trends and give real-time insights and actionable recommendations for brands. The platform can also turn insights into action by seamlessly executing these recommendations across marketplace store fronts, brand.coms, social and conversational commerce, performance marketing, inventory management, warehousing, and last mile logistics - all of which impacts a brand’s bottom line, driving profitable growth.

Roles & Responsibilities:

Work on implementation of real-time and batch data pipelines for disparate data sources.

• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies.
• Build and maintain an analytics layer that utilizes the underlying data to generate dashboards and provide actionable insights.
• Identify improvement areas in the current data system and implement optimizations.
• Work on specific areas of data governance including metadata management and data quality management.
• Participate in discussions with Product Management and Business stakeholders to understand functional requirements and interact with other cross-functional teams as needed to develop, test, and release features.
• Develop Proof-of-Concepts to validate new technology solutions or advancements.
• Work in an Agile Scrum team and help with planning, scoping and creation of technical solutions for the new product capabilities, through to continuous delivery to production.
• Work on building intelligent systems using various AI/ML algorithms. 

Desired Experience/Skill:

• Must have worked on Analytics Applications involving Data Lakes, Data Warehouses and Reporting Implementations.
• Experience with private and public cloud architectures with pros/cons.
• Ability to write robust code in Python and SQL for data processing. Experience in libraries such as Pandas is a must; knowledge of one of the frameworks such as Django or Flask is a plus.
• Experience in implementing data processing pipelines using AWS services: Kinesis, Lambda, Redshift/Snowflake, RDS.
• Knowledge of Kafka, Redis is preferred
• Experience on design and implementation of real-time and batch pipelines. Knowledge of Airflow is preferred.
• Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)