Data Engineer
Hi Role- Data Engineer Location- Chicago, Illinois (Hybrid) Mode- Contract Only W2 Job Description Top Skills' Details 1.
Proficiency in SQL, Stored Procedures, ETL, data warehousing, and data marts.
2.
Experience with Azure Data Factory for data orchestration, including integrating data using APIs 3.
Function Apps with Python code Job Description 70% Data Engineering, ETL, and Azure Data Factory Designing, building, and maintaining scalable and efficient data pipelines to extract, transform, and load (ETL) data from various sources into Azure data warehouses using Azure Data Factory.
Designing and implementing data marts, including dimensional modeling, schema design, and optimization techniques.
Integrating and consolidating data from diverse sources, such as databases, 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 Operations and Infrastructure teams to identify, design, and implement internal process improvements:
e.
g.
, automating manual processes, optimizing data delivery, and redesigning infrastructure for greater scalability.
Partners with Operations and Infrastructure teams to build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Azure Data Factory.
Understands how Harrison Street's data platform integrates within the overall technical architecture.
20% Data Visualization Solid understanding of data visualization principles, best practices, and design aesthetics.
Develop, maintain, and manage advanced reporting, analytics, dashboards using Tableau.
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.
10% Project Management 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.
Harrison Street is a leading investment management firm exclusively focused on alternative real assets.
Since inception in 2005, the Firm has invested $55 billion across senior housing, student housing, healthcare delivery, life sciences, data centers and storage real estate, as well as social and utility infrastructure.
We continue to innovate with this unrivaled network throughout North America and Europe.
Under direction of the Head of Data Analytics & Architecture, Global, the successful Data Engineer candidate will be responsible for designing, building, and maintaining 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 the core data domains of business intelligence, data science, data engineering, and data visualization.
The candidate will analyze the data needs of Harrison Street and use their skills in coding to develop and maintain secure data platforms.
The successful candidate will be responsible for transforming data into format(s) that can be more easily analyzed by citizen analysts and data scientists alike.
They will do this by developing, maintaining, and testing infrastructures for data generation that enable others within Harrison Street to more easily access in a secure way the data needed to derive data-driven insights and do their jobs.
The Data Engineer will be responsible for the collection, storage, processing, and transformation of large volumes of data to make it accessible, reliable, and usable for analysis and decision-making purposes.
The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.
The successful candidate must be self-directed and comfortable supporting the data needs of multiple teams and systems.
The right candidate will be excited by the prospect of optimizing our company's data to support our next generation of investments.
Additional Skills & Qualifications Qualifications Microsoft Certified Azure Data Engineer.
Experience using Tableau 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.
They should also have experience using the following software/tools:
Experience with 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.
IT Technical Recruiter Phone :
E mail:
Gtalk:
Recommended Skills Api Algorithms Analytical Architecture Big Data Building Codes Apply to this job.
Think you're the perfect candidate? Apply on company site $('.
external-apply-email-saved').
on('click', function (event) window.
ExternalApply = window.
open('/interstitial?jobdid=j3p1yy78y699m4586fx', 'ExternalApply-j3p1yy78y699m4586fx'); ); Estimated Salary: $20 to $28 per hour based on qualifications.
Proficiency in SQL, Stored Procedures, ETL, data warehousing, and data marts.
2.
Experience with Azure Data Factory for data orchestration, including integrating data using APIs 3.
Function Apps with Python code Job Description 70% Data Engineering, ETL, and Azure Data Factory Designing, building, and maintaining scalable and efficient data pipelines to extract, transform, and load (ETL) data from various sources into Azure data warehouses using Azure Data Factory.
Designing and implementing data marts, including dimensional modeling, schema design, and optimization techniques.
Integrating and consolidating data from diverse sources, such as databases, 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 Operations and Infrastructure teams to identify, design, and implement internal process improvements:
e.
g.
, automating manual processes, optimizing data delivery, and redesigning infrastructure for greater scalability.
Partners with Operations and Infrastructure teams to build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Azure Data Factory.
Understands how Harrison Street's data platform integrates within the overall technical architecture.
20% Data Visualization Solid understanding of data visualization principles, best practices, and design aesthetics.
Develop, maintain, and manage advanced reporting, analytics, dashboards using Tableau.
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.
10% Project Management 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.
Harrison Street is a leading investment management firm exclusively focused on alternative real assets.
Since inception in 2005, the Firm has invested $55 billion across senior housing, student housing, healthcare delivery, life sciences, data centers and storage real estate, as well as social and utility infrastructure.
We continue to innovate with this unrivaled network throughout North America and Europe.
Under direction of the Head of Data Analytics & Architecture, Global, the successful Data Engineer candidate will be responsible for designing, building, and maintaining 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 the core data domains of business intelligence, data science, data engineering, and data visualization.
The candidate will analyze the data needs of Harrison Street and use their skills in coding to develop and maintain secure data platforms.
The successful candidate will be responsible for transforming data into format(s) that can be more easily analyzed by citizen analysts and data scientists alike.
They will do this by developing, maintaining, and testing infrastructures for data generation that enable others within Harrison Street to more easily access in a secure way the data needed to derive data-driven insights and do their jobs.
The Data Engineer will be responsible for the collection, storage, processing, and transformation of large volumes of data to make it accessible, reliable, and usable for analysis and decision-making purposes.
The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.
The successful candidate must be self-directed and comfortable supporting the data needs of multiple teams and systems.
The right candidate will be excited by the prospect of optimizing our company's data to support our next generation of investments.
Additional Skills & Qualifications Qualifications Microsoft Certified Azure Data Engineer.
Experience using Tableau 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.
They should also have experience using the following software/tools:
Experience with 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.
IT Technical Recruiter Phone :
E mail:
Gtalk:
Recommended Skills Api Algorithms Analytical Architecture Big Data Building Codes Apply to this job.
Think you're the perfect candidate? Apply on company site $('.
external-apply-email-saved').
on('click', function (event) window.
ExternalApply = window.
open('/interstitial?jobdid=j3p1yy78y699m4586fx', 'ExternalApply-j3p1yy78y699m4586fx'); ); Estimated Salary: $20 to $28 per hour based on qualifications.
|
|
 | |
