Data Engineer

Harrison Street Asset Management ("HSAM") is a leading global alternative investment management firm focused on real estate, infrastructure, and credit strategies across North America and Europe. Headquartered in Chicago, Toronto, and London with offices across North America, Europe, Asia and the Middle East, the firm has over $108 billion in assets under management on behalf of institutional investors and registered investment advisors globally. Founded on a culture of innovation, HSAM is an early mover in alternative real estate and mid-market infrastructure. Today, the firm’s global team of more than 520 professionals is committed to creating long-term value through deep sector expertise and forward-thinking strategies.

About the role

Under the direction of the Head of Data Analytics & Architecture, Global, the successful Data Engineer candidate will design, build, and maintain the data infrastructure and systems that support data-driven applications and analytics within Harrison Street. The candidate must have a broad understanding of the entire data & analytics ecosystem of tools and technologies, with hands-on experience across business intelligence, data architecture, data science, data engineering, and data visualization.

The Data Engineer will analyze Harrison Street’s data needs and use coding skills to develop and maintain secure data platforms. They will transform data into formats easily analyzed by citizen analysts and data scientists, enabling secure access to data-driven insights. The role involves collecting, storing, processing, and transforming large volumes of data to make it accessible, reliable, and usable for analysis and decision-making.

The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. They must be self-directed, comfortable supporting the data needs of multiple teams, and excited by the prospect of optimizing the company’s data to support next-generation investments.

Harrison Street requires candidates to have independent, long-term work authorization that does not require future sponsorship or reliance on a third-party immigration process.

Responsibilities

• 60% Data Engineering, Data Architecture, and ETL
  • Design, build, and maintain scalable and efficient data pipelines to extract, transform, and load (ETL) data from various sources into the Enterprise Data Platform (EDP).
  • Design and implement data marts, including dimensional modeling, schema design, and optimization techniques.
  • Integrate and consolidate data from diverse sources (databases, SFTPs, APIs, streaming platforms), ensuring data quality, consistency, and integrity.
  • Create and maintain data models, defining data structures, relationships, and storage requirements using techniques like entity-relationship diagrams and data flow diagrams.
  • Develop data transformation processes, including data cleansing, normalization, aggregation, and enrichment, to prepare data for analytics and reporting.
  • Identify and resolve performance bottlenecks in data processing and storage systems, optimizing query performance and improving overall data pipeline efficiency.
  • Implement data quality assurance processes, perform data validation, test data pipelines, and resolve data quality issues.
  • Monitor data pipelines, diagnose and troubleshoot issues, and perform system upgrades and maintenance to ensure data reliability and availability.
  • Collaborate with cross-functional teams (Business Liaisons, analysts, software engineers) and document data engineering processes, workflows, and best practices.
  • Support training of Harrison Street team members on organizing findings and interpreting data.
  • Partner with Technology Infrastructure and Support Operations teams to identify, design, and implement internal process improvements (e.g., automating manual processes, optimizing data delivery, redesigning infrastructure for scalability).
  • Build infrastructure for optimal extraction, transformation, and loading of data from a wide variety of sources using Microsoft Fabric.
  • Understand how Harrison Street’s data platform integrates within the overall technical architecture.
• 20% Data Visualization
  • Apply a solid understanding of data visualization principles, best practices, and design aesthetics.
  • Develop, maintain, and manage advanced reporting, analytics, and dashboards using Tableau and Power BI.
  • Perform data analysis and validations.
  • Translate business requirements into technical solutions and communicate effectively with stakeholders.
  • Drive actionable insights through data analysis and interpretation.
• 10% Project Management
  • Work closely with stakeholders to define project goals, scope, and deliverables.
  • Create project plans, tasks, and timelines using Azure DevOps.
  • Monitor progress to ensure timely completion of milestones and deliverables.
  • Conduct meetings, provide progress reports, and manage expectations to ensure alignment and stakeholder satisfaction.
  • Develop risk mitigation and contingency plans to address potential setbacks.
  • Apply organizational and communication skills to meet project objectives and deliver high-quality results within defined constraints.
• 5% Cybersecurity Collaboration
  • Collaborate with the Cybersecurity team to adhere to organizational security standards, secure coding practices, and compliance requirements.
  • Work jointly with Cybersecurity teams on authentication, authorization, identity management, and secure Enterprise Data Platform development.
• 5% Miscellaneous
  • Stay current on emerging technologies for data architecture, data engineering, cloud services, security practices, and AI platform capabilities.
  • Document system configurations, platform architectures, processes, and operational procedures.
  • Participate in training, workshops, and internal knowledge-sharing sessions.
  • Perform other duties as assigned to support evolving business and technology needs.

Requirements

• Microsoft Certified – Fabric Data Engineer or Azure Data Engineer.
• Experience using Tableau and/or Power BI.
• Advanced working SQL knowledge and experience with relational databases, query authoring (SQL), and familiarity with a variety of databases.
• Experience building and optimizing Azure Data Factory pipelines, architectures, and datasets.
• Experience performing root cause analysis on internal and external data and processes to answer business questions and identify improvement opportunities.
• Strong analytic skills related to working with unstructured datasets.
• Experience building processes supporting data transformation, data structures, metadata, dependency, and workload management.
• A successful history of manipulating, processing, and extracting value from large, disconnected datasets.
• Strong organizational skills and experience supporting cross-functional teams in a dynamic environment.
• 5+ years of experience in a Data Engineer role.
• Experience with the following software/tools:
  • Microsoft Fabric or Azure Data Factory.
  • Relational SQL databases.
  • Azure cloud services.
  • Object-oriented/object-function scripting languages: Python, Java, C++, Scala, etc.
  • Compiling and organizing statistical information and presenting findings to management.
• Experience working with private and sensitive personal information.
• Confidence in decision-making and the ability to explain processes or choices as needed.
• Strong computer skills and proficiency with necessary databases and software.
• Ability to complete milestones and work toward multiple deadlines simultaneously.
• Proficiency in data warehousing solutions and ETL tools.
• Proficiency in database design, data definition, data dictionary, and related concepts.
• Understanding of Machine Learning, data APIs, app/dev & SDLC, algorithms, and data structures.
• Ability to evaluate technical problems and determine solutions.
• Strong written and verbal communication skills.
• Ability to follow and apply established security policies, procedures, and standards.
• Ability to read and understand technical manuals and vendor documentation.
• Ability to manage multiple technical workstreams independently.
• Ability to maintain professional and effective working relations with supervisors and co-workers.
• Flexibility to work evenings and weekends as needed.
• Ability to learn new skills and technologies.

Pay

$125,000 - $200,000 a year (base salary). For Illinois candidates, the expected base salary range is $125,000 to $200,000. Actual salaries may vary based on skills, experience, and qualifications. Total compensation includes a generous discretionary bonus and a comprehensive range of benefits—medical, financial, and wellness programs—to support employees professionally and personally.