Data Engineer, 2, Senior

Summary

The Data Engineer is responsible for transforming raw data from an organization s many data sources into a format that is more valuable to the enterprise. The Data Engineer will design efficient data models, build complex data pipelines, deliver high-impact dashboards and data visualizations, and construct solutions that facilitate self-service analytics. 

What You'll Do

• Administrating the data ecosystem, installing, configuring, managing, and upgrading technologies leveraged for analytics   

• Designing, testing, building, and managing complex, high-performing multi-user analytic solutions   

• Designing the modern data environment, including data processing and storage systems used to capture, ingest, refine, secure, and deliver data, utilizing both on-premises and cloud options   

• Coordinating technical interactions between information technology groups on environment and project matters   

Long Description

Key Responsibilities

• Power BI: Design, develop, and maintain Power BI dashboards and reports to meet business requirements, providing insightful data visualizations that support decision-making. Optimize Power BI solutions for performance, scalability, and maintainability while collaborating with business users to gather and define reporting requirements.
• SQL: Write, optimize, and maintain complex SQL queries for data extraction, transformation, and loading (ETL) processes, developing stored procedures, functions, and triggers to automate data processing tasks.
• Data Modeling: Develop and maintain data models to support reporting and analytics needs, ensuring data quality and integrity through thorough data analysis and profiling.
• Data Warehouse Management: Oversee delivery of consistent, accurate, and repeatable information through standard reports and dashboards, driving brand strategy and integrated marketing communications.

• Advanced Analytics: Utilize a wide range of statistical and multivariate analyses to provide both descriptive and exploratory insights, using speed and agility to evaluate uncertain conditions and outcomes, essential for predictive modeling and future forecasting.
• Data Stewardship: Ensure the proper management and use of data within the organization by implementing data stewardship practices. Establish and enforce data policies, standards, and procedures to maintain data quality, integrity, and security. Collaborate with data owners, business users, and IT teams to define data stewardship roles and responsibilities and promote a culture of data accountability and continuous improvement in data management practices.
• Communication: Communicate analytical results to business partners in a consultative manner, tailored to the target audience (both technical and non-technical audiences). You will also ensure the “Voice of the Customer” is represented in outputs, leveraging market segmentation to reflect customer behaviors and preferences in reporting, analysis, and measurement activities.

• Consultation with Business Partners: Collaborate with key cross-functional stakeholders to create robust data views, results, and insights.

Experience

• For an associate level, a minimum of no previous years of experience to two years related experience plus a bachelor's degree is required. (If no degree, four-six years of relevant experience or equivalent combination of education and related experience totaling four years.) • For a journey level, a minimum of two years of experience to four years related experienced plus a bachelor's degree is required. (If no degree, six years-eight of relevant experience or equivalent combination of education and related experience totaling six years.) • For a senior level, a minimum of five years of related experience plus a bachelor's degree is required. (If no degree, nine years of relevant experience or equivalent combination of education and related experience totaling nine years.)

Education