DATA ENGINEER (Senior Manager)

Data Engineer Senior Manager

Responsibilities

• Lead the design, development, and implementation of innovative data and software solutions that drive digital transformation and business value.
• Serve as the technical owner and solution lead for complex engineering initiatives, providing direction across architecture, design, development, testing, and deployment.
• Design scalable, resilient, and maintainable application, data, and integration architectures that align with business requirements and technology standards.
• Lead enterprise-scale data engineering solutions on modern cloud data platforms and lakehouse architectures, such as Databricks, Microsoft Fabric, Snowflake, Sigma, or similar enterprise data platforms.
• Design and implement scalable data pipelines, data products, APIs, integrations, and distributed data processing solutions using Python, SQL, Spark, and modern cloud technologies.
• Apply data modeling techniques and architectural patterns including data lake, lakehouse, Delta Lake, and data warehouse solutions to support analytics and AI-driven platforms.
• Collaborate with stakeholders to translate business and functional requirements into technical specifications, solution designs, and implementation roadmaps.
• Drive technical decision-making across architecture, engineering, integration, performance optimization, and operational readiness.
• Conduct architecture reviews, solution reviews, and code reviews to ensure adherence to engineering standards, security requirements, and software quality best practices.
• Champion modern engineering practices including CI/CD, DevOps, Infrastructure as Code (IaC), automated testing, observability, and deployment automation.
• Design and implement AI-enabled solutions using Generative AI, Retrieval-Augmented Generation (RAG), semantic search, vector databases, and agentic AI frameworks.
• Apply analytical thinking and systems thinking to troubleshoot complex technical challenges, identify dependencies, and drive root-cause resolution.
• Build and maintain strong client and stakeholder relationships, validate delivery outcomes, and incorporate feedback to continuously improve solutions.
• Promote innovation through rapid experimentation, proof of concepts, reusable accelerators, and adoption of emerging technologies.
• Coach and mentor engineers and technical leads through architecture guidance, design reviews, engineering practices, and technical problem solving.
• Own end-to-end technical delivery and solution outcomes, ensuring alignment with business objectives, quality standards, scalability requirements, and client expectations.

What You Must Have

• Bachelor’s degree or equivalent experience.
• 13 to 18 years of relevant experience in data engineering or related technology roles.

What Sets You Apart

• Deep expertise in Application Architecture, Data Engineering, Solution Design, and Technical Leadership.
• Proven experience architecting and delivering enterprise-grade applications, data platforms, integrations, and analytics solutions.
• Strong hands-on experience with modern cloud data platforms such as Databricks, Microsoft Fabric, Snowflake, Sigma, or similar enterprise data platforms.
• Expertise in Data Lakes, Lakehouse Architecture, Data Warehousing, Data Modeling, and Distributed Data Processing Frameworks.
• Advanced proficiency in Python, SQL, Spark, API Management, Enterprise Application Integration, and Modern Software Engineering Practices.
• Demonstrated expertise in CI/CD, DevOps, automated testing, deployment automation, and engineering governance.
• Experience designing and implementing Generative AI, Retrieval-Augmented Generation (RAG), semantic search, vector database architectures, and AI-powered enterprise solutions.
• Hands-on experience with modern AI orchestration and agentic frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, or similar technologies.
• Exceptional analytical thinking, systems thinking, and problem-solving capabilities with the ability to navigate highly complex and ambiguous technical challenges.
• Demonstrated ability to lead technical discussions, influence architecture and design decisions, and drive technical excellence across multiple initiatives.
• Strong client engagement and relationship management skills with the ability to translate complex technical concepts into business outcomes.
• Proven ability to innovate through rapid experimentation, creativity, and adoption of emerging technologies.
• Demonstrated ownership mindset with accountability for architecture quality, solution design, technical delivery, and business outcomes.
• Strong communication skills with the ability to effectively convey impactful technical and business messages across engineering, leadership, and client stakeholders.