Request Technology - Craig Johnson
Chicago, Illinois
*We are unable to sponsor for this permanent Full time role* *Position is bonus eligible* Prestigious Financial Company is currently seeking a Principal Data Analytics ETL Analyst. Candidate will be responsible for expanding the analytics capabilities by making data accessible and usable to analysts throughout the organization. In this role you will lead the design and build of our internal analytics data warehouse and the maintenance of the supporting extract, load, and transform processes. You will demonstrate and disseminate expertise in data sets and support teams across the organization in successfully harnessing this data. You will collaborate with business users and technical teams across the organization to facilitate data-driven decision making by enabling exploration and analysis of historical and near Real Time data access using cloud-based tools and technologies. Lastly, you will be responsible for gathering requirements and designing solutions that address the problem at hand while also anticipating yet-to-be-asked analytical questions and developing and maintaining our analytics platform to meet the company's security and IT standards. Responsibilities: Partner with Data Architecture and other relevant teams to design and implement new cloud data warehouse infrastructure for internal facing analytics Work with various business and functional teams to understand their data and technical requirements and ensure delivered solutions address needs Manage the validation of data models to ensure information is available in our analytics warehouse for downstream uses, such as ad hoc analysis and dashboard development Maintain performance requirements of our analytics warehouse by tuning warehouse optimizations and storage processes Direct and enable the team to collaborate with Data Governance team and DBAs to design access controls around our analytics warehouse to meet business and Data Governance needs Approve documentation and testing to ensure data is accurate and easily understandable Promote self-service capabilities and data literacy for business users leveraging the platform through development of training presentations and resources Discover and share best practices for data and analytics engineering with members of the team Invest in continued learning on data and analytics engineering best practices and evaluate them for fit in improving maintainability and reliability of analytics infrastructure Qualifications: [Required] Ability to collaborate with multiple partners (eg, Business Functional areas, Data Platform, Platform Engineering, Security Services, Data Governance, Information Governance, etc.) to craft solutions that align business goals with internal security and development standards [Required] Ability to communicate technical concepts to audiences with varying levels of technical background and synthesize non-technical requests into technical output [Required] Comfortable supporting business analysts on high-priority projects [Required] High attention to detail and ability to think structurally about a solution [Required] Knowledge of and experience working with analytics/reporting technology and underlying databases [Required] Strong presentation and communication skills, including ability to clearly explain deliverables/results to non-technical audiences [Required] Experience working within an agile environment= Technical Skills: Demonstrated proficiency in: [Required] Experience implementing and maintaining cloud-based data warehouses and curating a semantic layer that meets the needs of business stakeholders [Required] Knowledge of and experience working with various analytics/reporting technologies [Required] Strong presentation and communication skills, including ability to clearly explain deliverables/results to non-technical audiences [Required] Ability to complete work iteratively in an agile environment [Required] Proficiency in SQL [Preferred] Experience with Python and/or R [Preferred] Experience with visualization/reporting tools, such as Tableau [Preferred] Experience with ETL tools, such as Alteryx Education and/or Experience: [Required] Bachelor's degree in quantitative discipline (eg, Statistics, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent professional experience [Preferred] Master's degree [Required] 10+ years of experience as a data engineer, analytics engineer, Business Intelligence analyst, or data scientist Certificates or Licenses: [Preferred] Cloud platform certification [Preferred] BI tool certification
03/02/2025
Full time
*We are unable to sponsor for this permanent Full time role* *Position is bonus eligible* Prestigious Financial Company is currently seeking a Principal Data Analytics ETL Analyst. Candidate will be responsible for expanding the analytics capabilities by making data accessible and usable to analysts throughout the organization. In this role you will lead the design and build of our internal analytics data warehouse and the maintenance of the supporting extract, load, and transform processes. You will demonstrate and disseminate expertise in data sets and support teams across the organization in successfully harnessing this data. You will collaborate with business users and technical teams across the organization to facilitate data-driven decision making by enabling exploration and analysis of historical and near Real Time data access using cloud-based tools and technologies. Lastly, you will be responsible for gathering requirements and designing solutions that address the problem at hand while also anticipating yet-to-be-asked analytical questions and developing and maintaining our analytics platform to meet the company's security and IT standards. Responsibilities: Partner with Data Architecture and other relevant teams to design and implement new cloud data warehouse infrastructure for internal facing analytics Work with various business and functional teams to understand their data and technical requirements and ensure delivered solutions address needs Manage the validation of data models to ensure information is available in our analytics warehouse for downstream uses, such as ad hoc analysis and dashboard development Maintain performance requirements of our analytics warehouse by tuning warehouse optimizations and storage processes Direct and enable the team to collaborate with Data Governance team and DBAs to design access controls around our analytics warehouse to meet business and Data Governance needs Approve documentation and testing to ensure data is accurate and easily understandable Promote self-service capabilities and data literacy for business users leveraging the platform through development of training presentations and resources Discover and share best practices for data and analytics engineering with members of the team Invest in continued learning on data and analytics engineering best practices and evaluate them for fit in improving maintainability and reliability of analytics infrastructure Qualifications: [Required] Ability to collaborate with multiple partners (eg, Business Functional areas, Data Platform, Platform Engineering, Security Services, Data Governance, Information Governance, etc.) to craft solutions that align business goals with internal security and development standards [Required] Ability to communicate technical concepts to audiences with varying levels of technical background and synthesize non-technical requests into technical output [Required] Comfortable supporting business analysts on high-priority projects [Required] High attention to detail and ability to think structurally about a solution [Required] Knowledge of and experience working with analytics/reporting technology and underlying databases [Required] Strong presentation and communication skills, including ability to clearly explain deliverables/results to non-technical audiences [Required] Experience working within an agile environment= Technical Skills: Demonstrated proficiency in: [Required] Experience implementing and maintaining cloud-based data warehouses and curating a semantic layer that meets the needs of business stakeholders [Required] Knowledge of and experience working with various analytics/reporting technologies [Required] Strong presentation and communication skills, including ability to clearly explain deliverables/results to non-technical audiences [Required] Ability to complete work iteratively in an agile environment [Required] Proficiency in SQL [Preferred] Experience with Python and/or R [Preferred] Experience with visualization/reporting tools, such as Tableau [Preferred] Experience with ETL tools, such as Alteryx Education and/or Experience: [Required] Bachelor's degree in quantitative discipline (eg, Statistics, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent professional experience [Preferred] Master's degree [Required] 10+ years of experience as a data engineer, analytics engineer, Business Intelligence analyst, or data scientist Certificates or Licenses: [Preferred] Cloud platform certification [Preferred] BI tool certification
NO SPONSORSHIP Associate Principal, Data Analytics Engineering SALARY: $110k flex plus 10% bonus LOCATION: Chicago, IL Hybrid 3 days in office and 2 days remote You will be expanding analytics capabilities to design and build internal analytics within data warehouse using on-premises and cloud-based tools. You will create dashboards or visualization using the tools tableau powerBI SQL Queries Alteryx Jira services now. GIT a big plus, AWS or loud data warehouse airflow bs degree masters preferred this is working for operational risk 5 years experience building dashboards any audit risk knowledge is a plus This role will drive a team responsible for expanding analytics capabilities by making internal corporate data accessible and usable to analysts throughout the organization. Primary Duties and Responsibilities: Work closely with data analyst and business stakeholders to understand their data needs and provide support in data access, data preparation, and ad hoc queries Automate data processes to reduce manual interventions, improve data processing efficiency and optimize data workflow for performance scalability Integrate data form multiple sources and ensure data consistency and quality Build data models to ensure information is available in our analytics warehouse for downstream uses, such as analysis and create dashboards or visualizations using Tableau, Power BI to present insights Maintain performance requirements of our analytics warehouse by tuning optimizations and processes Create documentation and testing to ensure data is accurate and easily understandable Promote self-service capabilities and data literacy for business users leveraging the platform through development of training presentations and resources Discover and share best practices for data and analytics engineering with members of the team Invest in your continued learning on data and analytics engineering best practices and evaluate them for fit in improving maintainability and reliability of analytics infrastructure Qualifications: Ability to collaborate with multiple partners (eg, Corporate Risk, Compliance, Audit, Production Operations, DBAs, Data Architecture, Security) to craft solutions that align business goals with internal security and development standards Ability to communicate technical concepts to audiences with varying levels of technical background and synthesize non-technical requests into technical output Comfortable supporting business analysts on high-priority projects. High attention to detail and ability to think structurally about a solution Experience working within an agile environment Technical Skills & Background Ability to write and optimize complex analytical (SELECT) SQL queries Experience with data viz/prep tools Tableau and Alteryx [Preferred] Experience with SaaS tools and their backends, such as Jira and ServiceNow [Preferred] Applied knowledge of Python for writing custom pipeline code (virtual environments, functional programming, and unit testing) [Preferred] Experience with a source code repository system (preferably Git) [Preferred] Familiarity with at least one cloud data platform, such as AWS or GCP [Preferred] Experience creating and/or maintaining a cloud data warehouse or database [Preferred] Exposure to data orchestration tools, such as Airflow [Preferred] Understanding of applied statistics and hands-on experience applying these concepts Bachelor's degree in quantitative discipline (eg, Statistics, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent professional experience 5+ years of experience as a business analyst, data analyst, data engineer, research analyst, data engineer, analytics engineer, Business Intelligence analyst, data analyst, data scientist, or research analyst
03/02/2025
Full time
NO SPONSORSHIP Associate Principal, Data Analytics Engineering SALARY: $110k flex plus 10% bonus LOCATION: Chicago, IL Hybrid 3 days in office and 2 days remote You will be expanding analytics capabilities to design and build internal analytics within data warehouse using on-premises and cloud-based tools. You will create dashboards or visualization using the tools tableau powerBI SQL Queries Alteryx Jira services now. GIT a big plus, AWS or loud data warehouse airflow bs degree masters preferred this is working for operational risk 5 years experience building dashboards any audit risk knowledge is a plus This role will drive a team responsible for expanding analytics capabilities by making internal corporate data accessible and usable to analysts throughout the organization. Primary Duties and Responsibilities: Work closely with data analyst and business stakeholders to understand their data needs and provide support in data access, data preparation, and ad hoc queries Automate data processes to reduce manual interventions, improve data processing efficiency and optimize data workflow for performance scalability Integrate data form multiple sources and ensure data consistency and quality Build data models to ensure information is available in our analytics warehouse for downstream uses, such as analysis and create dashboards or visualizations using Tableau, Power BI to present insights Maintain performance requirements of our analytics warehouse by tuning optimizations and processes Create documentation and testing to ensure data is accurate and easily understandable Promote self-service capabilities and data literacy for business users leveraging the platform through development of training presentations and resources Discover and share best practices for data and analytics engineering with members of the team Invest in your continued learning on data and analytics engineering best practices and evaluate them for fit in improving maintainability and reliability of analytics infrastructure Qualifications: Ability to collaborate with multiple partners (eg, Corporate Risk, Compliance, Audit, Production Operations, DBAs, Data Architecture, Security) to craft solutions that align business goals with internal security and development standards Ability to communicate technical concepts to audiences with varying levels of technical background and synthesize non-technical requests into technical output Comfortable supporting business analysts on high-priority projects. High attention to detail and ability to think structurally about a solution Experience working within an agile environment Technical Skills & Background Ability to write and optimize complex analytical (SELECT) SQL queries Experience with data viz/prep tools Tableau and Alteryx [Preferred] Experience with SaaS tools and their backends, such as Jira and ServiceNow [Preferred] Applied knowledge of Python for writing custom pipeline code (virtual environments, functional programming, and unit testing) [Preferred] Experience with a source code repository system (preferably Git) [Preferred] Familiarity with at least one cloud data platform, such as AWS or GCP [Preferred] Experience creating and/or maintaining a cloud data warehouse or database [Preferred] Exposure to data orchestration tools, such as Airflow [Preferred] Understanding of applied statistics and hands-on experience applying these concepts Bachelor's degree in quantitative discipline (eg, Statistics, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent professional experience 5+ years of experience as a business analyst, data analyst, data engineer, research analyst, data engineer, analytics engineer, Business Intelligence analyst, data analyst, data scientist, or research analyst
*Hybrid, 3 days onsite, 2 days remote* *We are unable to sponsor as this is a permanent Full time role* A prestigious company is looking for a Principal, Data Analytics Engineering. This principal will lead the design and build of internal data analytics, data warehouse, and maintain ETL processes. They will also manage the validation of data models to make sure the information is available in analytics warehouse. Required: Financial industry experience, SQL, Python, Alteryx, Tableau. Responsibilities: Partner with Data Architecture and other relevant teams to design and implement new cloud data warehouse infrastructure for internal facing analytics Manage the validation of data models to ensure information is available in our analytics warehouse for downstream uses, such as ad hoc analysis and dashboard development Maintain performance requirements of our analytics warehouse by tuning warehouse optimizations and storage processes Direct and enable the team to collaborate with Data Governance team and DBAs to design access controls around our analytics warehouse to meet business and Data Governance needs Approve documentation and testing to ensure data is accurate and easily understandable Promote self-service capabilities and data literacy for business users leveraging the platform through development of training presentations and resources Discover and share best practices for data and analytics engineering with members of the team Invest in continued learning on data and analytics engineering best practices and evaluate them for fit in improving maintainability and reliability of analytics infrastructure Qualifications: Bachelor's degree in quantitative discipline (eg, Statistics, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent professional experience 10+ years of experience as a data engineer, analytics engineer, Business Intelligence analyst, or data scientist Experience implementing and maintaining cloud-based data warehouses and curating a semantic layer that meets the needs of business stakeholders Proficiency in SQL Experience with Python and/or R Experience with visualization/reporting tools, such as Tableau Experience with ETL tools, such as Alteryx Ability to collaborate with multiple partners (eg, Business Functional areas, Data Platform, Platform Engineering, Security Services, Data Governance, Information Governance, etc.) to craft solutions that align business goals with internal security and development standards Knowledge of and experience working with analytics/reporting technology and underlying databases Experience working within an agile environment
03/02/2025
Full time
*Hybrid, 3 days onsite, 2 days remote* *We are unable to sponsor as this is a permanent Full time role* A prestigious company is looking for a Principal, Data Analytics Engineering. This principal will lead the design and build of internal data analytics, data warehouse, and maintain ETL processes. They will also manage the validation of data models to make sure the information is available in analytics warehouse. Required: Financial industry experience, SQL, Python, Alteryx, Tableau. Responsibilities: Partner with Data Architecture and other relevant teams to design and implement new cloud data warehouse infrastructure for internal facing analytics Manage the validation of data models to ensure information is available in our analytics warehouse for downstream uses, such as ad hoc analysis and dashboard development Maintain performance requirements of our analytics warehouse by tuning warehouse optimizations and storage processes Direct and enable the team to collaborate with Data Governance team and DBAs to design access controls around our analytics warehouse to meet business and Data Governance needs Approve documentation and testing to ensure data is accurate and easily understandable Promote self-service capabilities and data literacy for business users leveraging the platform through development of training presentations and resources Discover and share best practices for data and analytics engineering with members of the team Invest in continued learning on data and analytics engineering best practices and evaluate them for fit in improving maintainability and reliability of analytics infrastructure Qualifications: Bachelor's degree in quantitative discipline (eg, Statistics, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent professional experience 10+ years of experience as a data engineer, analytics engineer, Business Intelligence analyst, or data scientist Experience implementing and maintaining cloud-based data warehouses and curating a semantic layer that meets the needs of business stakeholders Proficiency in SQL Experience with Python and/or R Experience with visualization/reporting tools, such as Tableau Experience with ETL tools, such as Alteryx Ability to collaborate with multiple partners (eg, Business Functional areas, Data Platform, Platform Engineering, Security Services, Data Governance, Information Governance, etc.) to craft solutions that align business goals with internal security and development standards Knowledge of and experience working with analytics/reporting technology and underlying databases Experience working within an agile environment