Lead Databricks Data Engineer

Company

Qualcomm India Private Limited

Job Area

Information Technology Group, Information Technology Group > IT Data Engineer

General Summary

We are looking for a Senior Data Engineer to design, build, and operate a modern, scalable data platform with Databricks Lakehouse as a core foundation. In this role, you will focus on building reusable data frameworks, shared platform components, and standardized pipelines that enable teams to deliver data products efficiently and consistently. Your work will support analytics, reporting, and downstream advanced use cases (including AI and machine learning), with a strong emphasis on reliability, governance, developer productivity, and intelligent automation.

Strong technical role with ownership across data engineering, framework development, AI driven automation, platform reliability, security, and cost management, while contributing to architectural decisions and data standards.

Data Engineering, Frameworks & AI Driven Automation

• Design, build, and maintain scalable batch and streaming data pipelines
• Develop reusable data engineering frameworks, libraries, and templates for ingestion, transformation, validation, and publishing
• Establish standardized patterns for data modeling, transformations, and pipeline orchestration
• Implement end-to-end data workflows from raw ingestion to curated analytical datasets
• Leverage AI based techniques to automate and optimize data engineering workflows, such as:
• Intelligent schema inference and evolution
• Automated data quality checks and anomaly detection
• Pipeline failure detection and self-healing mechanisms
• Experience building AI assisted or intelligent automation for:
• Data quality monitoring
• Pipeline observability
• Cost or performance optimization
• Ensure data quality, reliability, and performance across pipelines and shared frameworks
• Support downstream consumers such as analytics, reporting, and AI/ML teams

Reliability, Operations & Intelligent Automation

• Define and monitor SLIs/SLOs for data pipelines, frameworks, and platform availability
• Participate in incident response, on-call rotations, and post-incident reviews
• Apply AI assisted monitoring and alerting to proactively detect performance issues, data drift, and operational anomalies
• Implement security, compliance, and data governance controls across shared data assets
• Drive performance tuning and cost optimization, including automated recommendations for resource utilization and workload optimization

Collaboration & Technical Ownership

• Partner with analytics, application, and platform teams to understand common data needs and platform gaps
• Adopt standardized data frameworks, automation patterns, and best practices
• Contribute to data architecture decisions, platform standards, and design guidelines
• 7+ years of IT-related work experience in Data Platform with a Bachelor's degree.
• 7+ years of strong Data engineering experience with mandatory AI assisted development
• Hands-on technical experience with AWS, Databricks data platform ecosystem of Fivetran ingestion and Acceldata observability tools
• Solid hands-on experience in Data Engineering, Data Analysis, Data Modelling and enabling Analytics solutions
• Passion to explore emerging technologies and perform Proof Of Concepts (POC)
• Ability to work independently and collaborate with business and cross functional teams
• Accountability and Ownership of the delivery in driving the projects to completion

Data Engineering, Frameworks & System Design

• 7+ years of experience building and operating data platforms or distributed data systems
• Proven experience designing and building reusable data engineering frameworks, libraries, or platform components
• Strong experience designing scalable, reliable data pipelines using standardized patterns
• Solid understanding of data modeling, storage formats, schema evolution, and query performance
• Experience implementing automation in data pipelines, including rule based or AI assisted approaches
• Ability to reason about architectural trade-offs across scalability, cost, reliability, and security

Cloud & Data Platform Experience

• Strong hands-on experience with AWS, including IAM, networking, and multi-account setups
• Proven experience with Databricks Lakehouse, including Delta Lake and Unity Catalog
• Strong proficiency in Python for framework development, data processing, and automation
• Experience building data platforms that support multiple consumers and automated workflows

Security & Communication

• Understanding of cloud security best practices and data governance
• Experience working in regulated or compliance-driven environments
• Strong communication skills and the ability to drive adoption of shared frameworks and automation patterns across teams

Minimum Qualifications

• 4+ years of IT-related work experience with a Bachelor's degree in Computer Engineering, Computer Science, Information Systems or a related field.

OR

6+ years of IT-related work experience without a Bachelor’s degree.

• 2+ years of work experience with programming (e.g., Java, Python).
• 1+ year of work experience with SQL or NoSQL Databases.
• 1+ year of work experience with Data Structures and algorithms.

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