December 7
• DAS42 has multiple Data Engineer Consultant openings. • This person will be a key member of our consulting staff responsible for maintaining high delivery standards across an engagement team. • This individual will have the opportunity to work with various technologies and projects within a given client. • The ideal candidate enjoys learning new skills, contributing to the pre-sales process, working within a collaborative environment, and solving complex technical problems. • Develop system engineering, data integrations, based on client needs. • Implement data warehouse solutions, ETL pipelines, and business intelligence reporting tools. • Develop data models around stated use cases to capture client’s KPIs, data transformations, and data requirements; validation and testing of data models. • Support, maintain, and document clients’ data environments. • Contribute to and collaborate on project deliverables, either independently or as part of a larger consulting team. • Work within a project management framework (i.e., Agile) to meet objectives, understand scope, and impact of your work across an organization. • Guide clients on optimizing their data environment to operate most effectively and efficiently for them. • Clarify management objectives through data solutions. • Work with the Sales and Marketing teams to develop Thought Leadership and workable POCs and support our sellers by talking to clients about DAS42’s go-to-market capabilities.
• 3-7 years of work experience in a data analytics or data engineering role. • Advanced proficiency with Python and SQL. • Previously worked within a consulting/professional services environment (highly preferred) • Experience with business visualization tools (e.g. Looker, Tableau, Microsoft PowerBI). • Ability to explain technical concepts to non-technical people. • Experience with data warehousing and using Snowflake. • Experience with the AWS, Google Cloud ecosystem (e.g. BigQuery, Redshift). • Worked with or for Media & Entertainment or Telecom companies (preferred) • Bachelor's or Master’s degree in a quantitative field (i.e. Statistics or Operations Research) or technical field (i.e. Computer Science or Engineering). • A passion for exploring and solving different kinds of problems while learning and assimilating technical information quickly.
• Market driven and transparent compensation • Health and wellbeing benefits and policies • Organizational commitment to continual development • Impactful and meaningful experiences • Culture of ownership and autonomy
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