Assistant Vice President, Data Engineer

Harrison Street•Chicago, IL

3d•$125,000 - $200,000•Onsite

About The Position

Under direction of the Head of Data Analytics & Architecture, Global, the successful Full Stack Engineer candidate will be responsible for designing, building, and maintaining complete web applications, managing both front-end user interfaces and back-end server logic, databases, and APIs. They work throughout the entire software development lifecycle, from conception to deployment, ensuring applications are functional, responsive, and secure, while collaborating with teams to deliver seamless user experiences.

Requirements

Microsoft Certified – Fabric Data Engineer or Azure Data Engineer.
Experience using Tableau and/or Power BI.
Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
Experience building and optimizing Azure data Factory pipelines, architectures, and data sets.
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
Strong analytic skills related to working with unstructured datasets.
Build 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.
Experience supporting and working with cross-functional teams in a dynamic environment.
5+ years of experience in a Data Engineer role.
Experience with Microsoft Fabric or Azure Data Factory.
Experience with relational SQL databases.
Experience with Azure cloud services.
Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
Able to compile and organize statistical information retrieved and present findings to management.
Experience working with private and sensitive personal information.
Confident in decision making and the ability to explain processes or choices as needed.
Strong computer skills and ability to use necessary databases and software.
Ability to complete milestones and work toward multiple deadlines simultaneously.
Proficient in data warehousing solutions and ETL tools.
Proficient in database design, data definition, data dictionary, and related concepts.
Understands Machine Learning.
Can leverage data APIs.
Understands app/dev & SDLC.
Knowledge of algorithms and data structures.

Nice To Haves

Solid understanding of data visualization principles, best practices, and design aesthetics.
Ability to translate business requirements into technical solutions and effectively communicate with stakeholders.
Experience in data analysis and interpretation to drive actionable insights.
Apply organizational and communication skills to ensure project objectives are met, and deliverables are of high quality within the defined constraints.

Responsibilities

Designing, building, and maintaining scalable and efficient data pipelines to extract, transform, and load (ETL) data from various sources into Enterprise Data Platform (EDP).
Designing and implementing data marts, including dimensional modeling, schema design, and optimization techniques.
Integrating and consolidating data from diverse sources, such as databases, sftp’s, APIs, and streaming platforms, ensuring data quality, consistency, and integrity.
Creating and maintaining data models, defining data structures, relationships, and data storage requirements, using techniques like entity-relationship diagrams and data flow diagrams.
Developing data transformation processes, including data cleansing, normalization, aggregation, and enrichment, to prepare data for analytics and reporting.
Identifying and resolving performance bottlenecks in data processing and storage systems, optimizing query performance, and improving overall data pipeline efficiency.
Implementing data quality assurance processes, performing data validation, testing data pipelines, and resolving data quality issues.
Monitoring data pipelines, diagnosing and troubleshooting issues, performing system upgrades and maintenance tasks to ensure data reliability and availability.
Collaborating with cross-functional teams, including Business Liaisons, analysts, and software engineers, and documenting data engineering processes, workflows, and best practices.
Supports training of Harrison Street team members on how to properly organize findings and read data collected.
Partners with Technology Infrastructure and Support Operations team to identify, design, and implement internal process improvements: e.g., automating manual processes, optimizing data delivery, and redesigning infrastructure for greater scalability.
Partners with Technology Infrastructure and Support Operations teams to build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Microsoft Fabric.
Understands how Harrison Street’s data platform integrates within the overall technical architecture.
Develop, maintain, and manage advanced reporting, analytics, dashboards using Tableau and Power BI.
Perform data analysis and validations.
Ability to translate business requirements into technical solutions and effectively communicate with stakeholders.
Experience in data analysis and interpretation to drive actionable insights.
Work closely with stakeholders to define project goals, scope, and deliverables.
Create project plans, tasks, and timelines using Azure Dev Ops.
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 ensure project objectives are met, and deliverables are of high quality within the defined constraints.
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.
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.