Lead Databricks Architect – Financial Services & Banking

Sutherland•Dallas, TX

18d

About The Position

Sutherland is seeking an experienced Lead Databricks Architect with deep expertise in banking and financial services to lead the strategy, design, and implementation of an enterprise lakehouse platform. The role connects banking business requirements with data architecture and is responsible for building a secure, scalable, high-performance Databricks environment that supports regulatory reporting, risk management, fraud detection, customer analytics, and real-time transaction processing. The architect will design Databricks Lakehouse solutions using Delta Lake, Unity Catalog, and Databricks SQL; establish batch and streaming pipeline patterns; and lead migrations from legacy data platforms. The role also covers security, regulatory compliance, governance, data engineering standards, performance optimization, and automation across multi-cloud or hybrid-cloud environments. The Lead Databricks Architect partners with data science, quantitative analytics, BI, business, risk, and compliance teams, while providing technical leadership and mentorship to engineering and analytics teams.

Requirements

At least 5 years of hands-on experience designing and operating large-scale Databricks environments in production.
Deep knowledge of AWS, Azure, or GCP data services, such as Azure Data Lake Storage/Data Factory, AWS S3/Glue, or GCP GCS/BigQuery.
Mastery of Delta Lake, PySpark, Databricks SQL, Structured Streaming, and Delta Live Tables.
Strong hands-on experience configuring Unity Catalog, RBAC, ABAC, and data governance frameworks.
Proficiency with Terraform, CI/CD pipelines, and Databricks Asset Bundles.
At least 3 years of experience working within a retail bank, investment bank, or financial services institution.
Familiarity with core banking operations and financial data structures, including payments, lending, credit risk, anti-money laundering, or fraud.
Strong understanding of banking data compliance requirements, auditability, and data sovereignty standards.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related quantitative field, or equivalent practical experience.

Nice To Haves

Databricks Certified Data Engineer Professional certification.
Cloud Solutions Architect certification, such as AWS Certified Solutions Architect or Azure Solutions Architect Expert.

Responsibilities

Design and implement an enterprise-grade Databricks Lakehouse architecture using Delta Lake, Unity Catalog, and Databricks SQL tailored to financial data models.
Establish architectural patterns for high-throughput batch and real-time streaming pipelines integrating core banking systems, payment gateways, and third-party data providers.
Drive migration strategies from legacy data warehouses and platforms, including Teradata, Oracle, Snowflake, and mainframe environments, to Databricks.
Implement data security, enterprise access controls, and fine-grained permissions using Unity Catalog to support compliance with financial regulations such as GDPR, SOX, and PCI-DSS.
Architect data masking, tokenization, and encryption strategies for personally identifiable information and sensitive personal data.
Ensure data lineage, auditing, and metadata management across multi-cloud or hybrid-cloud Azure environments.
Define PySpark, Delta Live Tables, and SQL optimization practices to improve compute efficiency and reduce total cost of ownership.
Establish CI/CD, DevOps, and MLOps automation for code deployment, data quality validation, and model lifecycle management.
Partner with data science, quantitative analytics, and BI teams to support financial modeling, predictive risk analysis, and customer 360 initiatives.
Collaborate with business leaders, Chief Risk Officers, and compliance teams to align platform capabilities with banking objectives.
Provide technical leadership, mentorship, and architecture governance to data engineering and analytics teams.