I&F Decision Sci Practitioner Assoc Mgr

Accenture in India; Gurugram District; Presencial; INR 2.400.000 - 4.200.000; Jornada completa

Descripción de la vacante

Accenture in India seeks an experienced Data Engineer to design and optimize scalable data pipelines and architecture, improving data flow and supporting analysts and data scientists across multiple initiatives.

The TRWW BIA Data Engineer will be part of the TR Business Analytics Competency Center, delivering reliable data solutions for cross-functional teams in a self-directed role.

Formación

• Databricks, Python, SQL, Azure, PySpark and data engineering skills required.
• Experience in designing scalable data pipelines and working with data platforms.
• Ability to collaborate with analytics teams and stakeholders across functions.
• Knowledge of FMCG/supply chain domain is advantageous.

Responsabilidades

• Build and optimize reliable, scalable data pipelines
• Design data models (conceptual, logical, physical)
• Create complex datasets meeting business and technical requirements
• Develop solutions using Databricks, Python, SQL, Azure, and PySpark
• Automate processes and improve data delivery
• Monitor data quality and pipeline performance
• Collaborate across teams while prioritizing technical decisions independently

Conocimientos

Databricks

Python

SQL

Azure

PySpark

Stakeholder management

Communication

Independent work

Educación

Bachelor's degree in IT

Herramientas

Azure Data Factory

Control-M

Azure Blob Storage

Data Lake Storage

Key Vault

Erwin Data Modeler

Descripción del empleo

Skill required: Delivery - Data Analytics
Designation: I&F Decision Sci Practitioner Assoc Mgr
Qualifications:Any Graduation/Bachelors of Information Technology
Years of Experience:10 to 14 years

About Accenture

Accenture is a global professional services company with leading capabilities in digital, cloud and security.Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song— all powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. Our 784,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.Visit us at www.accenture.com

What would you do?

Accenture is a global professional services company specializing in strategy, consulting, technology, operations, digital, cloud, and security services. With approximately 699,000 employees serving clients in 120+ countries, Accenture helps organizations drive innovation and create value through technology and human ingenuity. Visit us at www.accenture.com. The TRWW BIA Data Engineer will design and optimize scalable data pipelines and architecture, improve data flow, and support analysts and data scientists across multiple initiatives. The role is part of the TR Business Analytics Competency Center and requires a self-directed professional who can deliver reliable data solutions for cross-functional teams.

What are we looking for?

• Databricks, Python, SQL, Microsoft Azure, PySpark
• Use Azure Data Factory and Control-M for pipelines and workflows
• Use Azure Blob Storage, Data Lake Storage, and Key Vault
• Experience with Spark Streaming; Azure streaming preferred
• Exposure to Kafka, SAP data, and Erwin Data Modeler is desirable
• Strong project, organizational, communication, and stakeholder-management skills
• Work independently, take initiative, and collaborate globally
• Knowledge of FMCG or beauty, supply chain, finance, sales, or marketing is advantageous Roles and Responsibilities:
• Build and optimize reliable, scalable data pipelines
• Design conceptual, logical, and physical data models
• Create complex datasets meeting business and technical requirements
• Develop solutions using Databricks, Python, SQL, Azure, and PySpark
• Automate processes, improve data delivery, and scale infrastructure
• Resolve data issues and support stakeholder infrastructure needs
• Build reusable tools for analytics and data science teams
• Monitor data quality, pipeline performance, dependencies, and reliability
• Convert business needs into secure, maintainable production solutions
• Collaborate across teams while managing priorities and technical decisions independently