Technical Lead (Data & Mulesoft)

Bridgestone Americas; Bengaluru; On-site; INR 400,000 - 900,000; Full time

Job summary

Bridgestone Americas is seeking a Technical Lead for DATA & MULESOFT to design and deliver scalable data solutions across AWS and Databricks. You will mentor engineers, lead cross-functional teams, and establish architectural standards to ensure security, scalability and production readiness.

The role requires deep expertise in data engineering, Spark, PySpark, SQL and Python, plus hands-on experience with MuleSoft and CI/CD practices. Strong communication and Agile collaboration are essential.

Qualifications

• 8+ years in Data Engineering / Data Architecture with large datasets.
• 3+ years with Databricks, Spark, PySpark and performance tuning.
• Strong SQL and Python development and debugging skills.
• Experience with AWS services (S3, Lambda, RDS, Step Functions).
• Familiarity with data orchestration, monitoring and operational resilience.
• Experience with REST APIs and API integrations.

Responsibilities

• Design scalable, enterprise-grade data solutions on AWS and Databricks.
• Lead development and modernization of data products and platforms.
• Establish standards, reusable frameworks, and best practices.

Skills

Databricks

Apache Spark

PySpark

SQL

Python

AWS

REST APIs

Data orchestration

CI/CD

MuleSoft

Tools

MuleSoft

Azure DevOps

Job description

Technical Lead ( DATA & MULESOFT )

Overview Of Role

• Design and deliver scalable, enterprise-grade data solutions across AWS and Databricks, covering end-toend architecture, ingestion, data modeling, transformation, orchestration, APIs, and downstream integrations.
• Lead the development and modernization of high-volume, business-critical data products and platforms, translating complex business and technical requirements into secure, scalable, and maintainable solutions.
• Establish architectural standards, coding practices, reusable frameworks, and engineering best practices to drive consistency, quality, and maintainability.
• Define robust orchestration, monitoring, and operational patterns to ensure performance, scalability, reliability, resilience, and cost optimization.
• Provide hands‑on technical leadership across solution design, architecture reviews, code reviews, development, debugging, and complex technical decision‑making.
• Lead cross‑functional delivery across Product, Business, Architecture, Data, API, QA, and Platform teams within Agile environments.
• Drive data quality, governance, observability, security, and production readiness across data products and platforms.
• Mentor engineers and technical leads while promoting engineering excellence and continuous improvement.

Required Qualifications

• 8+ years of experience in Data Engineering / Data Architecture, including data modeling, database design, ETL/ELT, data ingestion, legacy system migration, and processing large-scale datasets.
• 3+ years of hands‑on experience with Databricks, Apache Spark, and PySpark, including Spark performance optimization.
• Strong hands‑on experience with AWS services including S3, Lambda, Aurora/RDS, Step Functions, and CloudWatch.
• Strong SQL and Python development skills with proven experience in developing, debugging, and optimizing data solutions.
• Experience designing and implementing robust data orchestration workflows, including scheduling, dependencies, retries, error handling, monitoring, and operational resilience.
• Strong understanding of software engineering practices, including coding standards, code reviews, testing, reusable frameworks, and development best practices.
• Experience with REST APIs and API integrations, including request/response flows, integration patterns, and downstream data integrations.
• Working knowledge of MuleSoft or similar API and integration platforms.
• Experience with CI/CD practices and tools such as Azure DevOps or equivalent platforms.
• Strong understanding of data quality, validation, reconciliation, monitoring, and production support practices.
• Experience creating, reviewing, and maintaining functional and technical documentation.
• Strong understanding of Agile methodologies, including sprint planning, backlog refinement, and iterative delivery.
• Proven experience working with and leading cross‑functional teams comprising Data Engineering, API, QA, Architecture, Product, and Business stakeholders.
• Proven experience leading, mentoring, and providing technical guidance to data engineers and technical leads.
• Excellent verbal and written communication skills, with the ability to effectively communicate complex technical concepts to both technical and business stakeholders.

Preferred Qualifications

• Understanding of AWS or similar cloud infrastructure optimization and cost management, including evaluating compute, storage, and processing options.
• Data engineer with API development experience.
• Experience with Redis or any in‑memory database.
• Relevant AWS Certifications in cloud computing, data engineering, and/or solutions architecture.
• 8 + years of experience writing and maintaining infrastructure code.
• 8 + years of experience using any automation tools and ADO CI/CD pipelines.