Data engineer- With Private wealth management exp

🌍 Remote, USA 🎯 Full-time 🕐 Posted Recently

Job Description

Job Description

The Data Engineer will support data engineering initiatives within client Private Wealth Management (PWM) domain. This role focuses on designing, building, and maintaining high-quality data pipelines and platforms that support portfolio management, client reporting, performance analytics, and regulatory reporting.

The ideal candidate will have strong experience working with financial data related to investments, portfolios, transactions, and client accounts, along with hands-on expertise in modern data engineering tools and frameworks.

Key Responsibilities

Design, develop, and maintain scalable data pipelines for PWM data including portfolios, holdings, transactions, performance, and client data

Work closely with PWM business teams, analysts, and downstream consumers to understand data requirements

Build and optimize ETL/ELT processes to ingest data from multiple sources (custodians, trading systems, market data providers)

Ensure data quality, accuracy, lineage, and reconciliation across financial datasets

Support data models used for reporting, analytics, and regulatory requirements

Collaborate with application development, QA, and infrastructure teams

Monitor, troubleshoot, and resolve data pipeline and production issues

Follow enterprise SDLC, data governance, security, and compliance standards

Required Qualifications

7+ years of experience as a Data Engineer

Strong experience in Private Wealth Management, Asset Management, or Investment Management

Hands-on experience with financial data domains such as portfolios, trades, transactions, performance, benchmarks, and client accounts

Strong SQL skills and experience with relational and analytical databases

Experience with ETL tools, data pipelines, and batch processing

Solid programming experience in Python, Java, or Scala

Experience with on-prem and/or cloud data platforms

Preferred Skills

Experience with data warehouses and data lakes

Familiarity with cloud platforms (AWS, Azure, or GCP)

Knowledge of market data feeds and custodial data

Experience with reporting and analytics tools

Strong understanding of data governance, controls, and reconciliation in financial systems

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