We have partnered with our client in their search for a Data Engineer.
The Data Engineer will play a critical role in building and leading the next generation of analytics capabilities, driving applications of data visualization, analytics, and data science with measurable business value.
Snowflake and PowerBI experience are must haves.
Responsibilities:
Building tools, platforms, and pipelines to enable teams to analyze data, build models and drive decisions clearly and cleanly
Collaborating across teams to drive the generation of data driven operational insights that translate to high value optimized solutions.
Codifying best practices for future reuse in the form of accessible, reusable patterns, templates, and code bases
Assess and develop roadmap and capabilities for high priority data visualization and analytics use cases, including establishing and supporting strategic priorities and designing operational processes for BI, data science, Client, and AI.
Lead the entire delivery lifecycle of use case development from scoping and designing solutions to scaling from pilots to broader rollout.
Work collaboratively across teams to design and deliver solutions that drive measurable business results.
Translate business analytics problems into technical solutions that yield actionable recommendations
Qualifications:
Bachelor's degree in computer science, Information Technology, Computer Engineering or related IT discipline or professional work experience
10+ years of hands-on BI experience
Developing visual reports, KPI (Key Performance Indicator) scorecards, and dashboards using Power BI desktop.
Connecting data sources, importing data, and transforming data for Business intelligence.
Experience of 5+ years and familiarity with Microsoft Business Intelligence Stack having Power BI, SSAS, SSRS, SSIS, and DAX.
Extensive knowledge in data engineering including design, development and implementation of complex systems and data pipelines.
Keen understanding of retail domain with the ability to identify high opportunity areas and design approaches and solutions that generate and capture value.
Hands on evaluation experience with understanding of data exploration, model comparison, model evaluation, insights/interference, and data Interpretation / insight analysis.
Experience with solution design and development, quality assurance and testing, data visualization and prototyping.
