The Role
Design, build, and maintain data solutions and ETL pipelines on Databricks. Develop FastAPI-based microservices and REST/async APIs to serve data and GenAI applications, integrate LLMs and vector stores for RAG workflows, ensure performance, security, observability, and optimize Spark/PySpark jobs and Delta Lake lakehouse pipelines.
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 : Python Frameworks, Databricks Unified Data Analytics Platform, Generative AI
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
We are looking for a strong Backend Engineer (L8) with expertise in FastAPI and microservices-based architecture, complemented by data engineering capabilities on Databricks and exposure to GenAI application development.
The role will focus on building API-driven backend services for both traditional data platforms and GenAI-powered applications, enabling scalable data access, orchestration, and AI-driven solutions.
1. Backend Engineering (Primary – FastAPI)
Design and develop scalable, high-performance FastAPI-based microservices
Build RESTful APIs for:
Data access services
Metadata exposure
Workflow orchestration
Implement asynchronous APIs for long-running and high-concurrency workloads
Ensure API reliability, security, observability (logging, monitoring, tracing)
Develop reusable frameworks, middleware, and service templates
2. GenAI Application Development (New – Critical Skill)
Build backend APIs using FastAPI to support GenAI use cases, including:
Prompt orchestration and request routing
Integration with LLM services (Azure OpenAI / OpenAI / similar platforms)
Develop APIs that: Handle context-aware queries (RAG patterns)
Interface with vector stores / embeddings (via Databricks or external systems where applicable)
Implement multi-step workflows for GenAI applications (e.g., chaining, reasoning pipelines)
Ensure secure, scalable, and performant serving of GenAI models via APIs
Incorporate handling of: Latency optimization
Request throttling / token usage considerations (at API design level)
3. Data Engineering (Secondary – Databricks)
Develop and optimize data pipelines using Databricks / PySpark
Work with:
Delta Lake / Lakehouse architecture
Batch and near real-time pipelines
Support data ingestion, transformation, and provisioning layers
Optimize performance (partitioning, caching, tuning Spark jobs)
Enable integration between data pipelines and GenAI APIs (for RAG-based solutions)
Professional & Technical Skills:
- Must To Have Skills: Proficiency in Python Frameworks, Databricks Unified Data Analytics Platform, Generative AI.
- Strong experience in building scalable and reliable data pipelines using Python-based frameworks.
- In-depth knowledge of data processing techniques and best practices for data quality assurance.
- Familiarity with cloud-based data platforms and distributed computing environments.
- Ability to troubleshoot and optimize ETL workflows to improve performance and reliability.
- Experience working with large datasets and implementing data integration solutions.
Additional Information:
- The candidate should have minimum 7.5 years of experience in Python Frameworks.
- This position is based at our Pune 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 : Python Frameworks, Databricks Unified Data Analytics Platform, Generative AI
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
We are looking for a strong Backend Engineer (L8) with expertise in FastAPI and microservices-based architecture, complemented by data engineering capabilities on Databricks and exposure to GenAI application development.
The role will focus on building API-driven backend services for both traditional data platforms and GenAI-powered applications, enabling scalable data access, orchestration, and AI-driven solutions.
1. Backend Engineering (Primary – FastAPI)
Design and develop scalable, high-performance FastAPI-based microservices
Build RESTful APIs for:
Data access services
Metadata exposure
Workflow orchestration
Implement asynchronous APIs for long-running and high-concurrency workloads
Ensure API reliability, security, observability (logging, monitoring, tracing)
Develop reusable frameworks, middleware, and service templates
2. GenAI Application Development (New – Critical Skill)
Build backend APIs using FastAPI to support GenAI use cases, including:
Prompt orchestration and request routing
Integration with LLM services (Azure OpenAI / OpenAI / similar platforms)
Develop APIs that: Handle context-aware queries (RAG patterns)
Interface with vector stores / embeddings (via Databricks or external systems where applicable)
Implement multi-step workflows for GenAI applications (e.g., chaining, reasoning pipelines)
Ensure secure, scalable, and performant serving of GenAI models via APIs
Incorporate handling of: Latency optimization
Request throttling / token usage considerations (at API design level)
3. Data Engineering (Secondary – Databricks)
Develop and optimize data pipelines using Databricks / PySpark
Work with:
Delta Lake / Lakehouse architecture
Batch and near real-time pipelines
Support data ingestion, transformation, and provisioning layers
Optimize performance (partitioning, caching, tuning Spark jobs)
Enable integration between data pipelines and GenAI APIs (for RAG-based solutions)
Professional & Technical Skills:
- Must To Have Skills: Proficiency in Python Frameworks, Databricks Unified Data Analytics Platform, Generative AI.
- Strong experience in building scalable and reliable data pipelines using Python-based frameworks.
- In-depth knowledge of data processing techniques and best practices for data quality assurance.
- Familiarity with cloud-based data platforms and distributed computing environments.
- Ability to troubleshoot and optimize ETL workflows to improve performance and reliability.
- Experience working with large datasets and implementing data integration solutions.
Additional Information:
- The candidate should have minimum 7.5 years of experience in Python Frameworks.
- This position is based at our Pune 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
- Proficiency in Python frameworks
- Experience with FastAPI and microservices architecture
- Experience with Databricks Unified Data Analytics Platform
- Experience with PySpark and Spark job optimization
- Experience with Delta Lake and Lakehouse architecture
- Experience integrating Generative AI / LLMs (Azure OpenAI, OpenAI, or similar)
- Experience with vector stores and embeddings for RAG workflows
- Ability to design and implement ETL/data pipelines and ensure data quality
- Familiarity with cloud-based data platforms and distributed computing environments
- Minimum 7.5 years of professional experience (Python frameworks experience emphasized)
- 15 years full time education
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.
-
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.
-
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.
