Job VC
Senior Data Engineer — Wealth / Asset Management
About the Project
We're looking for a Senior Data Engineer to support a client in the wealth/asset management space. This is a
long-term engagement (6+ months)
— you'll work on data integration, data platform modernization, and analytics/reporting enablement in an environment where data accuracy, quality, and governance are business-critical.
What You'll Do:
Design, build, and maintain scalable data pipelines from enterprise systems into analytics/reporting environments
Integrate data from SAP, CRM, portfolio management platforms, APIs, databases, and flat files
Build and optimize data models for BI, dashboards, and business analytics
Prepare clean, reliable datasets to support Tableau / Power BI reporting
Develop ETL/ELT workflows covering ingestion, transformation, validation, and reconciliation
Implement data quality checks, monitoring, and logging
Work with business stakeholders to translate reporting requirements into data models
Support migration and modernization of legacy reporting/data workflows into scalable architecture
Ensure data security, governance, and compliance aligned with financial industry standards
What We're Looking For:
5+ years of experience in data engineering, data warehousing, or analytics engineering
Strong SQL skills and experience designing analytical data models
Proven experience building ETL/ELT pipelines with structured business data
Hands-on experience with cloud data platforms: Snowflake, Databricks, BigQuery, Redshift, Azure Synapse, or similar
Experience integrating data from ERP/enterprise systems; SAP experience is a strong plus
Experience supporting BI tools such as Tableau, Power BI, or Looker
Solid understanding of data quality, lineage, governance, and access control
Experience with APIs, batch loads, scheduled jobs, and file-based integrations
Strong communication skills and ability to work in a client-facing environment
Nice to Have:
Background in wealth/asset management, private banking, investment management, or financial services
Experience with portfolio, holdings, transactions, performance, or client/advisor data
SAP BW / SAP HANA / SAP Datasphere
Python for data processing and automation
dbt, Airflow, Fivetran, Matillion, Informatica, Azure Data Factory, or AWS Glue
Experience with MDM, data catalogues, or data governance platforms
Understanding of financial, regulatory, or client reporting workflows