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Manager - Data Engineer
RTX
Bengaluru•Hybrid•12+ Yrs•Jun 28
Job description
Hybrid
Overview
Date Posted: 2026-06-24Country: IndiaLocation: IN-KA-BENGALURU-NORTHGATE Sy No 2/2 Venkatala Village SY NO 2/2 VENKATALA VILLAGE, Yelahanka HobliPosition Role Type: Hybrid
Responsibilities
- 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.
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.
- 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.
- Knowledge of Unity Catalog, Databricks Workflows, Delta Live Tables, and Databricks governance/security best practices.
- Exposure to Terraform, ARM Templates, Infrastructure as Code (IaC), and cloud automation frameworks.
- Familiarity with gas turbine engine, manufacturing, engineering, or operational data domains is a plus.
Benefits
- 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
- Full-time
- This position requires flexibility to support outside the regular office hours as per the need basis