*We are unable to sponsor for this permanent Full time role*

*Position is bonus eligible*

Prestigious Financial Company is currently seeking a Data Analytics Engineer. Candidate will join a team responsible for expanding the analytics capabilities by making internal corporate data accessible and usable to analysts throughout the organization. This role will be an active contributor to the design and build of our internal analytics data warehouse and the maintenance of the supporting extract, load, and transform processes. This role will also become an expert on corporate data sets and support teams across the organization in successfully harnessing this data. This role will drive a team to 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 on premise and cloud-based tools and technologies. This role will drive the team responsible for gathering requirements and designing solutions that address the problem at hand while also anticipating yet-to-be-asked analytical questions, as well as collaborating with team members in defining and owning processes for developing and maintaining our analytics platform to meet the company's security and IT standards.

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:

• [Required] 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
• [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] Experience working within an agile environment
• [Required] Ability to write and optimize complex analytical (SELECT) SQL queries
• [Required] Experience with data viz/prep tools (preferably 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
• [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] 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