Lead Data Engineer

Job Title : Lead Data Engineer– Wealth Management

Location : [Noida / Gurgaon / Remote]

Experience : 10+ years

Must Have : Wealth Management Domain

Job Summary :

We are seeking a highly skilled Lead Data Engineer with deep expertise in the Wealth Management domain to design, implement, and manage scalable data solutions.

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.