The Role
The Data Engineer designs, develops, and maintains data solutions, creating data pipelines, ensuring data quality, and implementing ETL processes across systems. Responsibilities include leading data architecture efforts, mentoring team members, and integrating AI technologies.
Summary Generated by Built In
Project Role : Data Engineer
Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.
Must have skills : Machine Learning (ML)
Good to have skills : NA
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As a Data Engineer, a typical day involves designing, developing, and maintaining comprehensive data solutions that support the generation, collection, and processing of data. This role requires creating efficient data pipelines and ensuring the integrity and quality of data throughout its lifecycle. The position also involves implementing processes to extract, transform, and load data, facilitating seamless migration and deployment across various systems. Collaboration with different teams to optimize data workflows and troubleshoot any issues is a key part of daily activities, ensuring that data infrastructure supports organizational needs effectively and reliably.
Roles & Responsibilities:
- Expected to be an SME, collaborate and manage the team to perform.
- Responsible for team decisions.
- Engage with multiple teams and contribute on key decisions.
- Provide solutions to problems for their immediate team and across multiple teams.
- Lead the design and implementation of scalable data architectures to support business objectives.
- Mentor junior team members to enhance their technical skills and professional growth.
- Coordinate cross-functional efforts to align data engineering initiatives with organizational goals.
- Architect modular, goal-driven agents with planning, memory, tool use, and context-aware reasoning using LangChain, LangGraph, CrewAI, AutoGen, or Semantic Kernel.
- Develop and optimize RAG pipelines — chunking strategies, hybrid retrieval, re-ranking, and grounding — on vector stores (Pinecone, Weaviate, Chroma, FAISS).
- Integrate LLM APIs from OpenAI, Anthropic Claude, and Google Gemini implement function calling, MCP tool integrations, and multi-step orchestration.
- Apply advanced prompt engineering build evaluation harnesses (RAGAS, DeepEval, Phoenix) to measure faithfulness, relevance, and hallucination rate.
- Collaborate with architects, product managers, and backend engineers to deliver scalable, secure, and observable AI services on AWS / GCP / Azure.
- Contribute to code reviews, LLMOps practices, and continuous learning on emerging agentic-AI research.
Professional & Technical Skills:
- Must To Have Skills: Proficiency in Machine Learning (ML).
- Strong experience in building and optimizing data pipelines and ETL processes.
- Knowledge of data storage solutions and database management systems.
- Ability to work with large datasets and ensure data quality and consistency.
- Familiarity with cloud platforms and distributed computing frameworks.
- Experience in troubleshooting and resolving data-related issues efficiently.
- Must-have skills: AI/LLM-based systems (agents, RAG, orchestration), AI platforms (OpenAI, Claude, Gemini, Azure OpenAI), LangChain / LangGraph / CrewAI, vector databases, Python, prompt engineering, evaluation frameworks, cloud deployment.
Additional Information:
- The candidate should have minimum 5 years of experience in Machine Learning (ML).
- This position is based at our Bengaluru office.
- A 15 years full time education is required.
15 years full time education
Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.
Must have skills : Machine Learning (ML)
Good to have skills : NA
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As a Data Engineer, a typical day involves designing, developing, and maintaining comprehensive data solutions that support the generation, collection, and processing of data. This role requires creating efficient data pipelines and ensuring the integrity and quality of data throughout its lifecycle. The position also involves implementing processes to extract, transform, and load data, facilitating seamless migration and deployment across various systems. Collaboration with different teams to optimize data workflows and troubleshoot any issues is a key part of daily activities, ensuring that data infrastructure supports organizational needs effectively and reliably.
Roles & Responsibilities:
- Expected to be an SME, collaborate and manage the team to perform.
- Responsible for team decisions.
- Engage with multiple teams and contribute on key decisions.
- Provide solutions to problems for their immediate team and across multiple teams.
- Lead the design and implementation of scalable data architectures to support business objectives.
- Mentor junior team members to enhance their technical skills and professional growth.
- Coordinate cross-functional efforts to align data engineering initiatives with organizational goals.
- Architect modular, goal-driven agents with planning, memory, tool use, and context-aware reasoning using LangChain, LangGraph, CrewAI, AutoGen, or Semantic Kernel.
- Develop and optimize RAG pipelines — chunking strategies, hybrid retrieval, re-ranking, and grounding — on vector stores (Pinecone, Weaviate, Chroma, FAISS).
- Integrate LLM APIs from OpenAI, Anthropic Claude, and Google Gemini implement function calling, MCP tool integrations, and multi-step orchestration.
- Apply advanced prompt engineering build evaluation harnesses (RAGAS, DeepEval, Phoenix) to measure faithfulness, relevance, and hallucination rate.
- Collaborate with architects, product managers, and backend engineers to deliver scalable, secure, and observable AI services on AWS / GCP / Azure.
- Contribute to code reviews, LLMOps practices, and continuous learning on emerging agentic-AI research.
Professional & Technical Skills:
- Must To Have Skills: Proficiency in Machine Learning (ML).
- Strong experience in building and optimizing data pipelines and ETL processes.
- Knowledge of data storage solutions and database management systems.
- Ability to work with large datasets and ensure data quality and consistency.
- Familiarity with cloud platforms and distributed computing frameworks.
- Experience in troubleshooting and resolving data-related issues efficiently.
- Must-have skills: AI/LLM-based systems (agents, RAG, orchestration), AI platforms (OpenAI, Claude, Gemini, Azure OpenAI), LangChain / LangGraph / CrewAI, vector databases, Python, prompt engineering, evaluation frameworks, cloud deployment.
Additional Information:
- The candidate should have minimum 5 years of experience in Machine Learning (ML).
- This position is based at our Bengaluru office.
- A 15 years full time education is required.
15 years full time education
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us at www.accenture.com
Equal Employment Opportunity Statement
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
Skills Required
- Minimum 5 years of experience in Machine Learning (ML)
- Proficiency in Machine Learning (ML)
- Strong experience in building and optimizing data pipelines and ETL processes
- Knowledge of data storage solutions and database management systems
- Familiarity with cloud platforms and distributed computing frameworks
- Ability to work with large datasets and ensure data quality and consistency
- Experience in troubleshooting and resolving data-related issues efficiently
- Must-have skills in AI/LLM-based systems, AI platforms, LangChain, vector databases, Python, prompt engineering
Accenture Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Accenture and has not been reviewed or approved by Accenture.
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Healthcare Strength — Pay is considered competitive when paired with robust insurance options and other perks that compare well with large consulting and IT services peers. Multiple national medical plan options plus dental and vision are positioned as a core strength of the overall package.
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Retirement Support — Retirement support is positioned as a standout feature through a 401(k) dollar-for-dollar match up to a set percentage after eligibility. The package is reinforced by additional financial programs such as savings tools and related resources.
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Parental & Family Support — Parental and caregiving supports are presented as a meaningful benefit differentiator through substantial paid parental leave and multiple caregiver-oriented programs. Backup care and fertility/adoption/surrogacy navigation and reimbursements add breadth to family support beyond leave alone.
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The Company
What We Do
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, Interactive, Technology and Operations services—all powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. Our 500,000+ 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.
