Position Summary

Job Description 

Summary/objective

As a Senior Data Analytics Engineer, you will design and build data solutions that span data engineering, data warehousing, data analytics, and data science in this multi-disciplinary role. You will lead engineering efforts to create and populate an enterprise data layer, partnering with the firm’s Data Architect to model a suitable data schema. You will interface directly with senior business leaders to identify a set of analytical requirements – supporting strategic objectives, operational efficiency, and growth of the firm – then define, build, maintain, and evolve a target technology solution architecture to enable the realization of those requirements. With the data layer in place, you will define, build, test, document, support, maintain, and evolve the descriptive and predictive analytics needed to supply the firm with data-driven insights.

As a successful candidate, you will bring a track record of engineering analytical solutions on modern data components (e.g., Microsoft data and analytics stack) that deliver business value. You will have experience selecting fit-for-purpose technology components that account for desired ROI/TCO and the avoidance of future technical debt, as well as an ability to elicit and translate business leaders’ data and information needs into a prioritized analytics roadmap. You will also bring sharp communication skills to garner support for technical and analytical recommendations.

Essential functions

Data Collection and Extraction:

• Lead data collection efforts associated with the enterprise data layer, gathering and aggregating data from diverse sources, databases, and systems
• Ensure data accuracy, integrity, and consistency through meticulous data cleaning and validation processes, in collaboration with the Data Architect and business stakeholders

Data Warehouse Management:

• Lead design and refinement of data storage architecture.
• Collaborate with Data Architect on data modeling tasks
• Define and lead technology proof of concepts to ensure feasibility of architecture solutions
• Define target state technology architecture and roadmaps
• Prepare and deliver comprehensive communications to convey architectural direction and alignment with enterprise strategy
• Maintain operations of data storage solution

Data Transformation:

• Lead and execute data mapping and data transformation efforts associated with the enterprise data layer, including translating target system data requirements into mapping and transformation specifications

Data Integration:

• Set priorities, expectations, and work with third party to successfully deliver on project work as well as maintain integrations to support data engineering tasks in the UHY environment.
• Responsible for existing integrations around the enterprise data layer; their proper function, and convening appropriate resources (individuals, teams) to troubleshoot, repair, and document proper function as well as repairs/fixes. Directly troubleshoot and repair integrations where necessary.
• Define and maintain integrations for new internal source systems and mergers and acquisitions activity.
• Maintain up-to-date knowledge of industry best practices for integration tools/toolsets.

Data Analysis and Advanced Modeling:

• Utilize statistical techniques, data analysis tools, and programming languages (e.g., Python, R, SQL) to perform in-depth analysis of complex datasets
• Develop and implement analytical models and algorithms to extract valuable insights

Data Visualization and Reporting:

• Work closely with various internal and external stakeholders to clarify business requirements, remove roadblocks, and aligns business vision into data strategy and solution
• Create sophisticated data visualizations, dashboards, and reports to communicate complex findings effectively
• Utilize data visualization tools such as Power BI or Excel

Data Interpretation:

• Collaborate with stakeholders to interpret data, providing actionable insights and recommendations
• Contribute to the development of data-driven strategies, goals, and solutions

Documentation and Best Practices:

• Maintain detailed documentation of data sources, methodologies, and analysis processes
• Lead individual or classroom trainings for users on data solutions, technologies, and functionality
• Promote best practices in data analysis, documentation, and knowledge sharing
• Guide source systems Data Stewards on data standards and maintenance of data dictionary.

Continuous Learning and Innovation:

• Stay at the forefront of industry trends, emerging data engineering/storage/analysis techniques, and tools
• Champion innovation by exploring new technologies and methodologies in data engineering, data warehousing/storage, data analytics operations, and data analysis

Mentorship and Collaboration:

• Mentor and guide junior data analysts, fostering their professional growth and development
• Collaborate closely with cross-functional teams, acting as a subject matter expert in data analysis

Supervisory responsibilities

• None

Work environment

• Work is conducted in a professional office environment with minimal distractions

Physical demands

• Prolonged periods of sitting at a desk and performing work in front of a computer screen for long periods of time
• Must be able to lift up to 15 pounds at a time

Travel required

• Occasional travel to conferences or to firm office sites may be required, approximately 5% of the time

Required education and experience

• Bachelor’s degree in data science, statistics, mathematics, computer science, business, or a related field
• Minimum of 8 years previous experience in the execution of data-oriented initiatives, such as creating or improving enterprise data components and analytics
• Proficiency in data modeling techniques and related tools
• Proficiency in data analysis tools, such as SQL
• Proficiency in data integration/engineering tools and approaches

Preferred education and experience

• Master's degree in data science, statistics, mathematics, computer science, business, or a related field
• Experience with the Microsoft data and analytics technology stack
• Experience with ML/AI models in supporting business analytics

Additional eligibility requirements

Other duties

Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time with or without notice.