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.

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