Delivery Lead – Data Engineering & Databricks (Architecture Focus) - Assistant Vice President

Role Summary & Role Description:

• The Delivery Lead will drive end-to-end delivery of data engineering platforms with a strong focus on Databricks and modern cloud-based architectures.
• This role combines delivery leadership with deep technical ownership of solution architecture, ensuring scalable, secure, and high-performing data solutions aligned to business outcomes.
• The individual will lead cross-functional global teams and act as a bridge between business stakeholders, architects, and engineering teams.

Key Responsibilities:

• Own and drive end-to-end delivery of data engineering and analytics initiatives with strong governance and execution discipline.
• Define and implement scalable data architecture using Databricks, cloud platforms, and big data technologies.
• Lead solution design discussions and translate business requirements into robust technical architecture.
• Establish delivery frameworks including Agile execution, release planning, and risk management.
• Provide leadership to globally distributed teams and ensure alignment across engineering, QA, and business teams.
• Drive stakeholder communication with clear reporting on delivery progress, risks, and mitigation plans.
• Promote engineering excellence, code quality, and performance optimization practices across teams.

Data Engineering & Databricks Expertise (Primary Skill):

• Strong hands-on experience with Databricks for building and managing data pipelines and workflows.
• Expertise in Spark (Python/Scala) and distributed data processing frameworks.
• Experience designing and implementing ETL/ELT pipelines on cloud platforms (AWS/Azure).
• Deep understanding of data lakehouse architecture, Delta Lake, and modern data platforms.
• Ability to optimize data processing performance, scalability, and cost-efficiency.
• Experience in data governance, lineage, metadata management, and regulatory compliance requirements.

Architecture & Design Skills:

• Proven experience in designing enterprise-scale data architecture and solutions.
• Strong understanding of data modeling (conceptual, logical, physical) and integration design patterns.
• Experience defining architecture standards, best practices, and design governance frameworks.
• Ability to evaluate and recommend modern data tools and frameworks based on business needs.
• Experience integrating on-premise systems with cloud-based data platforms.

Core / Must Have Skills:

• 15+ years of experience in technology delivery with strong leadership exposure.
• Extensive experience in Data Engineering and Big Data ecosystems (Hadoop, Spark, Databricks).
• Strong programming expertise in Python/Scala and SQL.
• Experience with cloud platforms such as AWS or Azure.
• Strong understanding of CI/CD, DevOps, and data pipeline automation.
• Excellent communication, stakeholder management, and leadership skills.

Good to Have Skills:

• Experience with Kafka or other streaming technologies.
• Knowledge of containerization tools such as Docker and Kubernetes.
• Exposure to financial services or regulatory reporting environments.
• Experience working in global, distributed teams across time zones.

Education & Experience:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• Proven experience leading large-scale transformation or data modernization programs.

About State Street

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