Senior/Lead Analytics Data Engineer ID19406
hace 6 días
We are a leading provider of custom software solutions, recognized as one of the Inc. 5000 fastest-growing companies in the US and a top-3 ranked dev shop according to Clutch.
We create award-winning software solutions that help companies across various industries drive business growth and improve lives.
Job SummaryWe are seeking a highly skilled Senior/Lead Analytics Data Engineer to join our team. As a key member of our data engineering team, you will be responsible for designing, developing, and maintaining large-scale data systems to support business intelligence and analytics needs.
Key Responsibilities- Data Modeling and Design
Develop and maintain conceptual, logical, and physical data models to support analytics and reporting needs.
Data Dictionary and Schema ManagementCreate and manage data dictionaries, ER diagrams, and schema designs that align with business requirements.
Collaboration and StandardsCollaborate with data architects and stakeholders to define data modeling standards and best practices.
Engineering and ReportingUtilize code (SQL, Python, etc.) and apply engineering, reporting, and visualization expertise to solve business problems. Develop scalable tools to drive automation and optimize business operations.
Team LeadershipDevelop and lead a team of junior data analysts, providing mentorship, training, and coaching to increase technical acumen across the team.
System DevelopmentDevelop scalable systems to expand reporting capabilities, facilitate ad hoc analysis, and improve data-driven decision-making at all levels of the business.
Data Analysis and TransformationWork with large, complex data sets. Solve difficult data transformation problems with efficiency, applying advanced analytical methods as needed. Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
Code Quality and DocumentationContribute to the establishment of standards for writing clean, organized code and documentation to streamline data and analytics workflow.
Culture and DiversityDrive and promote a culture of testing, observability, and scalability with a data-driven mindset. Actively participate in AgileEngine's diversity and inclusion agenda.
User Experience and EducationManage and continuously improve business user's experience with data and reporting, including KPI development, data visualization, and communication of applicable insights to audiences at varying levels of technical sophistication. Increase overall data literacy across AgileEngine through education and advocacy.
Partnerships and CollaborationDevelop partnerships with engineering, data science, and product teams to deliver on major cross-functional reporting, measurement, and testing efforts.
Requirements- Education
BS/BA in a quantitative field; a plus if MS degree in a quantitative discipline (e.g., Statistics, Operations Research, Economics, Computer Science, Mathematics, Engineering) or equivalent practical experience.
ExperienceProven experience as a Data Engineer, with a focus on analytics and data modeling.
SkillsStrong proficiency in SQL and experience with data modeling tools. Knowledge of programming languages such as Python, Java or Scala. Expertise in Google Cloud Platform (GCP) services, including BigQuery. Experience with ETL/ELT processes and tools.
Additional Requirements4+ years of hands-on experience in crafting compelling data visualizations to inform business decisions. 4+ years of experience in Data Warehouse Data Modeling techniques. Track record of delivering data-driven products and insights as well as influencing product and engineering decisions. Experience in analyzing, validating, and transforming large datasets. Familiarity with data governance, data quality, and data security best practices. Proficiency in deploying data-intensive solutions. Solid understanding of the software development lifecycle.
Nice to HaveExperience with DataPlex – big plus. Experience with analytics software such as Looker, PowerBI, Tableau, or similar open-source tools.
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