Vice President Data Engineer Jobs (NOW HIRING)

Role Overview

We are seeking an experienced Vice President - Data Engineer with 10-15 years of handson experience to lead the design, development, and optimization of scalable, cloudnative data platforms. This role requires deep technical expertise in Azure, Databricks, PySpark, Python, and SQL, supporting enterprise data pipelines for regulatory, compliance, and analytics workloads.

The ideal candidate will operate at both strategic and handson levels, delivering reliable, secure, and highperformance data solutions in a highly regulated investment banking environment.

Key Responsibilities

• Own the architecture, design, and implementation of endtoend ETL/ELT workflows using Azure Data Factory (ADF) and Azure Databricks for regulatory and compliancedriven data ingestion and transformation.
• Integrate, standardize, and normalize structured and unstructured data from multiple internal and external sources while enforcing strict data quality and governance controls.
• Build secure, auditable, and highperformance data pipelines supporting largescale, sensitive financial datasets.
• Automate ingestion, transformation, and validation processes to enable near realtime analytics and regulatory reporting.
• Design and implement efficient storage formats, partitioning, and optimization strategies for fast data access and retrieval.
• Utilize Databricks and Delta Lake for distributed processing, ACIDcompliant storage, versioning, and timetravel capabilities.
• Enforce data retention, archiving, and purging policies aligned with global regulatory and compliance requirements.
• Drive the migration of legacy application logic into modern Azure Databricks, Data Lake, and SQLbased architectures.
• Maintain comprehensive data lineage, metadata management, and audit trails using Azure Purview or equivalent frameworks.
• Partner with data governance, risk, and compliance teams to define data standards, access controls, and security requirements.
• Implement and manage CI/CD pipelines using GitHub and GitHub Actions, enabling automated testing, version control, and reliable deployments.
• Review code, enforce engineering best practices, and support production deployments and operational stability.
• Participate in Agile/Scrum ceremonies, including sprint planning, design reviews, and regulatory or audit engagements.
• Provide technical leadership and mentorship to data engineers, setting standards and best practices across the organization.

• Master's degree in Computer Science, Engineering, Information Systems, or a related field.
• 10-15 years of handson experience in data engineering, preferably within financial services or other regulated industries

Required Technical Expertise

• Azure Databricks (clusters, jobs, notebooks, Delta Lake, performance tuning)
• PySpark (RDDs, DataFrames, Spark SQL, optimization techniques)
• Azure Cloud Services:
• Azure Data Factory (ADF)
• ADLS Gen2
• Azure Synapse
• Azure Functions
• Azure DevOps / GitHub
• Python for data engineering and automation workflows
• SQL (complex queries, performance optimization, largescale datasets)

Preferred / NicetoHave Skills

• Experience designing and supporting enterprisescale ETL/ELT pipelines.
• Strong understanding of Delta Lake, medallion architecture (Bronze/Silver/Gold), and distributed data processing.
• Familiarity with data governance, security, encryption, and RBAC in cloudnative environments.
• Experience with CI/CD best practices and automated deployment pipelines.
• Exposure to BI and visualization tools such as Power BI or Tableau.
• Familiarity with Anaplan or other enterprise planning platforms is a plus, particularly in supporting downstream financial analytics or planning use cases.
• Exposure to or handson experience with AI agents, intelligent automation, or GenAIenabled data workflows is a strong plus.
• Excellent analytical, communication, and crossfunctional collaboration skills.