Sr. Data Engineer - FCP Tech

Federal Capital Partners

• $120K — $145K *
Real Estate & Construction
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's or advanced degree in Engineering or Computer Science with strong academic performance
  • 4+ years of relevant work experience
  • 2+ years of experience building and deploying data engineering solutions on cloud platforms (Azure preferred)
  • 2+ years of data analytics experience
  • 2+ years of experience with Python and associated data libraries
  • 2+ years of experience with databases and queries
  • Strong analytical skills to translate data into strategic insights

Responsibilities

  • Design and develop AI-assisted data pipelines and Power BI reports
  • Build, automate, and maintain data ingestion pipelines using Microsoft Fabric Data Factory and Python
  • Develop automated financial data analysis workflows leveraging AI and machine learning
  • Integrate and govern disparate financial and operational data sources
  • Lead data quality, reconciliation, and lineage initiatives across datasets

Benefits

  • Opportunity to work directly with firm leadership and industry experts
  • Access to cutting-edge tools and technologies
  • Collaborative and entrepreneurial work environment
  • Focus on professional growth and development
  • Engagement in impactful projects that drive business decisions
Full Job Description
We are currently seeking a Sr. Data Engineer to join our Washington, DC team. FCP's technology team is at the forefront of this transformation, leveraging AI, automation, and modern data platforms to drive smarter investment decisions and operational excellence. This role offers a unique opportunity to work directly with firm leadership, industry experts, and cutting-edge tools to make a measurable impact on the business.

RESPONSIBILITIES:

As a Sr. Data Engineer, you will support our business lines, clients and investment decisions by:
  • Design and develop AI-assisted data pipelines, semantic models, and Power BI reports to support investment decisions and operations
  • Build, automate, and maintain data ingestion pipelines using Microsoft Fabric Data Factory and Python
  • Develop automated financial data analysis workflows and reporting solutions that leverage AI and machine learning capabilities
  • Integrate and govern disparate financial and operational data sources within FCP's Microsoft Fabric lakehouse environment
  • Lead data quality, reconciliation, and lineage initiatives across investment, financial, and asset management datasets

REQUIREMENTS:
  • Bachelor's degree or advanced degree in Engineering or Computer Science with excellent academic credentials
  • Minimum of 4 years of relevant work experience
  • Minimum of 2 years of experience building and deploying data engineering solutions on cloud platforms (Azure preferred)
  • Minimum of 2 years of relevant data analytics work experience
  • Minimum of 2 years of experience with python and associated data libraries
  • Minimum of 2 years of experience with databases & queries
  • Ability to analyze qualitative and quantitative information and translate into strategic deliverables
  • Ability to work independently and within a team
  • Experience working in Microsoft Azure and/or Microsoft Fabric; familiarity with AI services such as Azure OpenAI strongly preferred
  • Excellent written and oral communication skills
  • Experience in presenting ideas and analysis to groups and leadership
  • Motivated self-starter with effective time management skills and strong attention to detail
  • A desire to work within a fast-paced, collaborative, and entrepreneurial environment
  • Experience or previous interest in Real Estate strongly preferred
  • Required Technical Skills:
    • Excel (Complex Formulas, PivotTables, Formatting)
    • Microsoft Fabric (Lakehouse, Data Factory, Notebooks)
    • Python
    • SQL
    • Power BI & DAX
  • Preferred Technical Skills:
    • Azure OpenAI & AI Services
    • Databricks
    • JavaScript/HTML/CSS
    • LangChain or other AI/LLM orchestration frameworks
    • Financial Modeling

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