Data Analytics Engineering

Posted 8 months ago
  • Principal, Data Analytics Engineering
  • Salary: $90K – 150k plus bonus
  • Location : Richmond, Virginia  
  • Hybrid 3 days in office and 2 days remote
  • Job ID: W2108783

Looking for a candidate with experience leading design and build internal data analytics, data warehouse and maintenance of ETL processes. data sets design implement new cloud data warehouse infrastructure for internal facing analytics manage the validation of data models design access controls around analytics warehouse to meet business a data governance must come from a financial firm with knowledge of capital markets organize data analytics SQL python r tableau ETL tools like alter yx driving enterprise analytics strategy

                        Responsibilities:

                    To perform this job successfully, an individual must be able to perform each primary duty satisfactorily.

                    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:

                    Ability to collaborate with multiple partners (e.g., 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

                    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

                    Experience working within an agile environment

                        Technical Skills:

                    Demonstrated proficiency in:

                    Experience implementing and maintaining cloud-based data warehouses and curating a semantic layer that meets the needs of business stakeholders

                    Knowledge of and experience working with various analytics/reporting technologies

                    Strong presentation and communication skills, including ability to clearly explain deliverables/results to non-technical audiences

                    Ability to complete work iteratively in an agile environment

                    Proficiency in SQL

                    Bachelor’s degree in quantitative discipline (e.g., Statistics, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent professional experience

                    8+ years of experience as a data engineer, analytics engineer, business intelligence analyst, or data scientist

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