Lead Data Engineer

Job Title:

Location:

Experience:

Must Have: Wealth Management Domain

Job Summary:

Lead Data Engineer

Experience in building end-to-end Data Lake and Modern Data Platform programs covering the full lifecycle from data ingestion (Bronze Layer) to curation and transformation (Silver Layer), and finally business-ready consumption (Gold Layer) for analytics, AI, and reporting. Work spans across greenfield builds, modernization, re-platforming, and AI/GenAI integrations.

Should understand Azure Data Lake, Azure Storage, Azure Data Factory (ADF), Azure Databricks, Azure Synapse Analytics (formerly Azure Data Warehouse), Azure Cognitive Services, and Azure OpenAI, now unified under Microsoft Fabric.

Wealth Management experience

Key Responsibilities:

• Lead the design and implementation of

  end-to-end data architecture

  for Wealth Management applications.
• Develop and maintain

  Data Lake

  and

  Data Fabric

  solutions to ensure seamless data integration, storage, and retrieval.
• Collaborate with business stakeholders to understand data requirements and translate them into robust data models and pipelines.
• Build

  data pipelines

  and ETL processes using

  Python

  and other modern data engineering tools.
• Ensure

  data quality, governance, and security

  across all data assets.
• Provide technical leadership and mentoring to junior data engineers and analysts.
• Evaluate and recommend emerging data technologies and best practices for continuous improvement.
• Work closely with analytics, AI/ML, and business intelligence teams to support advanced analytics initiatives.

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
• 8+ years of experience in

  data architecture, data engineering, or data management

  , preferably in the

  Wealth Management domain

  .
• Strong proficiency in

  Python

  for data processing, transformation, and analytics.
• Hands-on experience with

  Data Lake architectures

  (AWS, Azure, or GCP).
• Expertise in

  Data Fabric frameworks

  and data integration patterns.
• Solid understanding of relational and non-relational databases, data modeling, and metadata management.
• Experience with

  ETL/ELT pipelines

  , data pipelines orchestration (e.g., Airflow, Prefect).
• Familiarity with

  cloud-based data platforms

  and big data technologies.
• Excellent communication, problem-solving, and stakeholder management skills.

Preferred Skills:

• Experience with

  analytics, AI/ML integration

  , or business intelligence platforms.
• Knowledge of regulatory and compliance requirements in Wealth Management.
• Hands-on experience with

  Spark, Kafka, or other distributed data processing tools

  .

What We Offer:

• Opportunity to lead critical data initiatives in a high-impact Wealth Management environment.
• Collaborative and innovative work culture.
• Exposure to cutting-edge data technologies and cloud platforms.