Date Posted:

2026-06-24

Country:

India

Location:

IN-KA-BENGALURU-NORTHGATE ~ Sy No 2/2 Venkatala Village ~ SY NO 2/2 VENKATALA VILLAGE, Yelahanka Hobli

Position Role Type:

Hybrid

At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world’s most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world.

Pratt & Whitney is a world leader in the design, manufacture and service of aircraft engines and auxiliary power systems and has been revolutionizing modern flight for over 100 years. Join us and help shape the future of aerospace and defense.

What You will do :

Architect, design, and implement scalable cloud-based ETL/ELT solutions using Azure Data Platform technologies including Azure Databricks, PySpark, Azure Data Factory, ADLS, and related Azure services.
Design and implement enterprise-scale Lakehouse solutions using Medallion Architecture (Bronze, Silver, Gold layers) to support scalable, governed, and high-performance analytics platforms.
Provide strong hands-on expertise in PySpark-based distributed data processing and Databricks-based enterprise ETL development.
Develop metadata-driven and YAML-configured ETL frameworks to enable reusable, scalable, configurable, and standardized data pipeline implementations across enterprise projects.
Lead and mentor distributed engineering teams by providing technical guidance, delivery oversight, architecture direction, and best practices across data engineering initiatives.
Collaborate with business stakeholders, enterprise architects, product owners, and global technology teams to understand business priorities and design scalable cloud-native data solutions.
Drive stakeholder management activities including requirement discussions, solution walkthroughs, technical presentations, architecture reviews, risk mitigation, and delivery governance.
Build strong cross-functional relationships and ensure alignment between business, engineering, infrastructure, security, and governance teams.
Develop reusable ETL frameworks, coding standards, and best practices for enterprise-wide adoption across analytics and operational reporting initiatives.
Optimize Spark and Databricks workloads for scalability, reliability, performance tuning, and cost efficiency.
Implement robust data quality frameworks, validation rules, monitoring, observability, lineage, and logging mechanisms across enterprise data platforms.
Drive enterprise data governance, metadata management, master data management, and security best practices within modern data platform implementations.
Lead cloud modernization and migration initiatives from legacy/on-prem platforms to Azure-based modern Lakehouse architecture.
Design scalable curated data layers for reporting, analytics, AI/ML, and downstream enterprise applications.
Work closely with DevOps and infrastructure teams to implement CI/CD pipelines, YAML-based deployment automation, Infrastructure as Code (IaC), and environment management strategies.
Stay current with emerging technologies and recommend innovative approaches in Azure cloud architecture, Databricks, Spark optimization, and modern data engineering frameworks.
Function as a senior individual contributor while driving technical leadership, delivery excellence, collaboration, and architectural governance across programs.

Basic Qualifications:

B.E./B.Tech in Computer Science, Data Science, Engineering, Mathematics, Statistics, or related discipline with 12+ years of relevant experience OR Advanced Degree with 8+ years of relevant experience.
12+ years of experience in Data Engineering, ETL Development, Data Warehousing, and Enterprise Data Architecture.
Strong hands-on expertise in PySpark and Azure Databricks with proven experience designing and implementing enterprise-scale distributed data processing solutions.
Extensive experience architecting Azure cloud-based ETL solutions using Azure Databricks, Azure Data Factory, Azure Data Lake Storage (ADLS), Azure Synapse, Azure SQL, and related Azure services.
Strong expertise in Medallion Architecture, Delta Lake, Lakehouse concepts, and enterprise data platform design principles.
Hands-on experience with YAML-driven ETL frameworks, configuration-based pipeline development, CI/CD automation, and metadata-driven orchestration approaches.
Strong experience leading engineering teams, coordinating delivery activities, mentoring developers, and driving technical excellence across projects.
Experience with Azure DevOps, Git-based version control, CI/CD pipelines, Infrastructure as Code (IaC), and deployment automation frameworks.
Strong understanding of data modeling, metadata management, data governance, and enterprise architecture best practices.
Self-driven senior individual contributor with strong analytical and problem-solving capabilities.

Preferred Qualifications:

Experience implementing enterprise-scale Azure Modern Data Platform and Lakehouse solutions.
Knowledge of Unity Catalog, Databricks Workflows, Delta Live Tables, and Databricks governance/security best practices.
Experience working with real-time and streaming data processing frameworks.
Exposure to Terraform, ARM Templates, Infrastructure as Code (IaC), and cloud automation frameworks.
Experience in Aerospace & Defense, Manufacturing, Supply Chain, or Engineering data ecosystems.
Familiarity with gas turbine engine, manufacturing, engineering, or operational data domains is a plus.
Experience working in Agile and global delivery environments.

What We offer

Long-term deferred compensation programs
Daycare for young children
Advancement programs to enhance education skills
Flexible work schedules
Leadership and training programs
Comprehensive benefits, savings, and pension plans
Financial support for parental leave
Reward programs for outstanding work

Please ensure the role type defined below is appropriate for your needs before applying to this role. This position is classified as:

Role Type: Hybrid - Employees who are working in Hybrid roles will work regularly both onsite and offsite

Candidates will learn more about role type and current site status throughout the recruiting process.

Employment Type:

Full-time
This position requires flexibility to support outside the regular office hours as per the need basis

Video Links:

Pratt & Whitney - YouTube

RTX adheres to the principles of equal employment. All qualified applications will be given careful consideration without regard to ethnicity, color, religion, gender, sexual orientation or identity, national origin, age, disability, protected veteran status or any other characteristic protected by law.

Privacy Policy and Terms:

Click on this link to read the Policy and Terms

Manager - Data Engineer