Engineering Manager (Data + Mulesoft)

Engineering Manager

Location: Bangalore

Company: Bridgestone

Job Type: Full-Time

Role Overview

We are seeking an experienced Engineering Manager with 11+ years of experience to lead

engineering teams in delivering scalable, reliable, and customer-centric digital products.

This role combines technical leadership, team management, and delivery ownership. You

will work closely with Product, Design, Business, and global stakeholders to drive

execution excellence, foster engineering best practices, and ensure successful delivery of

high-impact technology solutions.

Key Responsibilities

Engineering Leadership

• Lead and mentor engineering teams across one or more product areas
• Drive the end-to-end delivery of customer-facing applications and platforms
• Ensure the development of scalable, secure, and high-quality software solutions
• Promote engineering best practices and a culture of continuous improvement

Technical Excellence

• Provide technical guidance on application architecture, microservices, cloud

technologies, Databricks and integrations.

• Drive adoption of modern engineering practices including CI/CD, DevOps,

automation, and observability

• Ensure application performance, reliability, maintainability, and security
• Support engineering teams in resolving complex technical challenges

Product & Delivery Ownership

• Collaborate with Product Managers, Designers, and Business stakeholders to

translate business requirements into technical solutions

• Own sprint planning, execution, release coordination, and delivery commitments
• Monitor project progress, manage risks, and ensure predictable execution
• Drive continuous improvement in delivery processes and engineering eOiciency

Global Collaboration

• Partner with global stakeholders, including teams in the US, to align priorities and

execution plans

• Facilitate cross-functional and cross-geography collaboration
• Support eOective communication and decision-making across teams

People Leadership

• Coach, mentor, and develop engineers and technical leads
• Support performance management, career development, and employee

engagement initiatives

• Build a culture of accountability, ownership, innovation, and teamwork
• Participate in hiring and onboarding of engineering talent

Operations & Support

• Support production applications and ensure platform stability
• Drive incident management, root cause analysis, and service improvements
• Ensure adherence to operational procedures, monitoring standards, and SLAs
• Promote proactive maintenance and operational excellence practices

Required Experience & Qualifications

Experience

• 10+ years of experience in software engineering
• 2+ years of experience leading engineering teams or managing technical projects
• Proven experience delivering scalable enterprise or SaaS applications
• Experience working with cross-functional and global teams
• Strong understanding of Agile development methodologies and delivery practices

Technical Expertise

Backend & Architecture

• Experience with Java and Spring Boot
• Experience designing and building microservices-based applications
• Strong understanding of distributed systems and API-driven architecture
• Experience with API design, development, and integrations

Frontend

• Experience with Angular and/or React .

Integration & Middleware

• Experience with MuleSoft for API management and enterprise integrations.
• MuleSoft Anypoint Platform, including API Manager, Runtime Manager, Anypoint

Exchange, and related platform capabilities.

Cloud & DevOps

• Experience with Amazon Web Services (AWS)
• Familiarity with Infrastructure as Code tools such as Terraform.
• Experience working with containers and orchestration platforms such as

Kubernetes/EKS.

• Exposure to CI/CD pipelines and DevOps practices.

Data & Persistence

• Experience with databases such as PostgreSQL, Aurora/Oracle.
• Strong understanding of data modeling and database performance optimization
• Experience with AWS services including S3, Glue, Aurora/RDS, Lambda, and Step

Functions, with a strong understanding of cloud-native data engineering practices.

• Experience with Databricks, Spark, and PySpark, including Spark performance

optimization, partitioning, joins, caching, file formats, data skew, and eOicient job

design.

• Strong SQL and Python/PySpark skills, with experience in data modeling, database

design, schema mapping, ETL/ELT, and source-to-target transformations.

• Experience designing and optimizing data pipelines and orchestration workflows,

including scheduling, dependencies, retries, error handling, monitoring, failure

recovery, and performance optimization.

• Strong understanding of software engineering practices including coding standards,

code reviews, testing, Git, CI/CD, Azure DevOps, reusable frameworks, and

automation.

• Experience with data quality, validation, reconciliation, monitoring, troubleshooting,

and root-cause analysis.

• Understanding of REST APIs, API request/response flows, and integration with APIs

and third-party source systems.

• Experience creating, reviewing, and maintaining functional and technical

documentation throughout the delivery lifecycle.

• Strong communication and collaboration skills, with experience working across

Product, Business, Architecture, QA, API, and Engineering teams in Agile

environments.

• Strong understanding of Agile practices, including sprint planning, backlog

refinement, estimation, iterative delivery, and production support.

Observability & Reliability

• Experience with monitoring, logging, and alerting solutions
• Understanding of production support, incident management, and system reliability

practices

• Ability to drive application performance and operational excellence initiatives

Leadership Expectations

• Strong communication and stakeholder management skills
• Ability to balance technical depth with delivery execution
• Passion for coaching, mentoring, and team development
• Collaborative and customer-focused mindset
• Strong analytical and problem-solving skills
• Data-driven approach to decision-making and prioritization