Accenture Applied Intelligence practice help our clients grow their business in entirely new ways.  Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition

As part of our Analytics practice, you will join a worldwide network of over 20,000 smart and driven colleagues experienced in leading statistical tools, methods and applications. From data to analytics and insights to actions, our forward-thinking consultants provide analytically-informed, issue-based insights at scale to help our clients improve outcomes and achieve high performance.

Manager in Applied Intelligence

A Data Engineering Manager(Full Stack & Cloud) defines and delivers scalable, secure cloud-native data platforms and end-to-end data products. They combine technical ownership across frontend/back-end/infra with people and program management — translating business priorities into architecture, driving cloud strategy, enforcing operational excellence, and coaching teams to deliver reliable data and ML-ready services that enable analytics and AI.

Duties and Responsibilities:

• Own the end-to-end data platform and full-stack data product roadmap: architecture, delivery, reliability, and cost-efficiency.
• Translate business requirements into scalable cloud architectures (data ingestion, processing, storage, APIs, and UIs) that serve analytics, reporting, and ML/GenAI needs.
• Drive design and implementation of batch and streaming pipelines, microservices, APIs, feature stores, vector DBs, and data stores (relational & NoSQL).
• Ensure resilient deployments via CI/CD, IaC, containerization (Docker/Kubernetes), serverless patterns, and orchestration (Airflow/ADF/other).
• Lead cloud cost optimisation, capacity planning, security, compliance, and data governance (lineage, cataloguing, access controls).
• Partner with Product, Data Science, Analytics, and Engineering to prioritise platform features, SLAs, and SLOs.
• Establish and enforce engineering best practices: code reviews, testing, observability, incident runbooks, and postmortems.
• Hire, mentor, and grow engineers and leads; allocate resources, set goals, and manage delivery across multiple pods.
• Drive migration/modernization initiatives (on-prem → cloud, monolith → microservices, legacy ETL → lakehouse) when applicable.
• Maintain stakeholder communication: status reporting, technical tradeoffs, risk mitigation, and roadmap alignment.

Educational Background/qualifications

• B Tech/M Tech from reputed engineering colleges
• Masters/M Tech in Computer Science
• Master degree in Statistics/Econometrics/ Economics from reputed institute

Requirements:

• 8–12+ years in software/data engineering and cloud platform roles, with 3+ years managing or leading engineering teams.
• Proven experience designing and operating cloud-native data platforms on AWS/Azure/GCP (or multiple).
• Strong full-stack capabilities: backend services (Python/Java/Scala/Go), frontend/web UI experience (React/Vue or similar) a plus, and robust API design.
• Deep experience with data technologies: Spark/Databricks, data lakes/lakehouses (Delta/Iceberg/Hudi), data warehouses (Snowflake/BigQuery/Redshift), streaming (Kafka/Kinesis), and feature stores/vector DBs.
• Expertise in infrastructure as code (Terraform/CloudFormation), container orchestration (Kubernetes), CI/CD pipelines, and automated testing.
• Solid understanding of security, identity/access management, encryption, and regulatory compliance for data.
• Experience with monitoring/observability tools, cost management, and SRE/ops practices.
• Strong stakeholder management, program delivery, and vendor evaluation experience.

Soft Skills

• Strategic thinker with a delivery mindset and strong bias for measurable outcomes.
• Excellent people manager and coach; fosters psychological safety and continuous learning.
• Clear, concise communicator able to translate technical tradeoffs to business stakeholders.

Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law.

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 

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