Azure Databricks Engineer (Wealth Management Platform)

[Tech Craft 360 LLC]

Please send profiles on man...@360techcraft.com 

Dear Candidates,

 

Please find the below JD for the role of Azure Databricks Engineer (Wealth Management Platform).

Role - Azure Databricks Engineer (Wealth Management Platform)

Location - Austin, TX (Hybrid)

Visa - GC/USC

Data Engineer — Wealth Management Platform

Data & Technology | Wealth Management Division

Department: Data Engineering     

About the Role

We are seeking a skilled Data Engineer with a strong wealth management background to join our data and technology team. This role sits at the intersection of financial data and modern cloud engineering — you will design, build, and maintain the data pipelines and infrastructure that power our advisor and client reporting, reconciliation processes, and platform integrations.

The ideal candidate brings hands-on experience with Databricks and the Microsoft cloud ecosystem, a deep understanding of wealth management data domains, and the ability to leverage AI tooling to accelerate their daily work.

Key Responsibilities

Data Pipeline Development & Engineering

• Design, build, and maintain scalable data pipelines using Databricks and Azure cloud services

• Develop and optimize PySpark and Python-based ETL/ELT workflows for ingesting, transforming, and serving wealth management data

• Build and manage data models that support advisor, account, client, position, transaction, and security datasets

• Ensure data pipelines meet performance, reliability, and latency requirements for downstream consumers

 

Financial Data & Reconciliation

• Reconcile financial datasets across custodians, internal systems, and third-party data providers — identifying and resolving breaks at the position, transaction, and account level

• Partner with operations and service teams to investigate and resolve data discrepancies impacting advisors and clients

• Implement data quality checks, validation rules, and alerting to proactively catch data integrity issues

• Support the build-out of reconciliation frameworks that scale across growing data volumes and entity counts

 

Cloud Infrastructure & Platform

• Build and manage data infrastructure on Microsoft Azure, including Azure Data Factory, Azure Data Lake, and related services

• Contribute to the architecture and governance of the data lakehouse environment within Databricks (Delta Lake, Unity Catalog)

• Collaborate with platform and DevOps teams on CI/CD pipelines, environment management, and data infrastructure as code

 

AI-Augmented Engineering

• Actively leverage AI coding assistants and automation tools (e.g., GitHub Copilot, Claude, ChatGPT) to accelerate development, code review, and documentation

• Identify opportunities to apply AI/ML techniques to financial data problems such as anomaly detection, break prediction, or data classification

• Stay current on emerging AI tooling and bring practical recommendations to the team

Required Qualifications

• 5–8 years of experience in data engineering, with direct exposure to wealth management data domains

• Databricks Certified (Associate or Professional) or demonstrated deep, hands-on Databricks expertise in a production environment

• Proficiency in Python and PySpark for building and optimizing large-scale data pipelines

• Hands-on experience with Microsoft Azure cloud services (Azure Data Factory, Azure Data Lake Storage, Azure Synapse, or equivalent)

• Direct experience working with wealth management data including positions, transactions, accounts, clients, advisors, and security master data

• Experience reconciling financial datasets across custodians, platforms, or internal systems

• Strong understanding of data modeling, ETL/ELT patterns, and data warehouse or lakehouse architecture

• Demonstrated use of AI tools in day-to-day engineering work — this is not optional; we expect engineers to be actively leveraging AI to move faster and work smarter

Preferred Qualifications

• Experience with Delta Lake, Unity Catalog, or Databricks Asset Bundles

• Familiarity with custodial data feeds and formats (Schwab, Fidelity, Pershing, or similar)

• Exposure to advisor technology platforms such as Addepar, Black Diamond, Envestnet, Orion, or Tamarac

• Experience with dbt (data build tool) for transformation layer development

• Knowledge of financial instruments including equities, fixed income, alternatives, and managed accounts

• Familiarity with data governance, data lineage, and metadata management practices

• Experience in a fintech, WealthTech, RIA, or asset management environment

Key Competencies

• Financial Data Fluency — You speak the language of wealth management data and understand what positions, transactions, and reconciliation breaks mean to the business

• Engineering Rigor — You write clean, testable, well-documented code and care about the reliability of what you build

• AI-Forward Mindset — You actively incorporate AI tools into your workflow and treat them as force multipliers, not novelties

• Cross-Functional Collaboration — You can work effectively with operations, service, and product teams to understand data needs and translate them into engineering solutions

• Problem Ownership — You don't just find issues in data; you see them through to resolution and build guardrails to prevent recurrence

Manvik
Tech Craft 360 LLC
262 CHAPMAN RD STE 240
NEWARK, DE 19702
Email – man...@360techcraft.com
https://360techcraft.com