We have a big vision which is why we need you—an innovator and problem solver ready to revolutionize and empower businesses to succeed.
Job Overview
As a Data Engineer in our growing Business Analytics & Data Platform teams, you will support developing and maturing a data-driven organization by creating intuitive means of accessing analytics by transforming data and developing, constructing, and testing cloud-based data architectures.
Collaborating with both data scientists, data engineers, business analytics stakeholders, and analytics developers; you will optimize the databases you work with using your knowledge of data warehouse solutions, data modeling, and ETL. Although not a data scientist, you’ll be fully integrated into our data science team and the modeling process, serving as an internal resource for all things data, advising on data quality issues, feature creation, and deployment best practices.
What You'll Do
Responsibilities:
- Build and maintain data systems and pipelines to transform legacy data structures distributed across dozens of cloud databases, on-prem databases, and a data warehouse into cleaned, well-organized, and documented data structures and data features ready for use by business analytics consumers and analysts
- Develop and maintain the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using primarily SQL Server, Databricks, and Azure technologies
- Use Python, Scala and SQL to assist with data cleaning, profiling, and exploration
- Collaborate with cross-functional business teams in Marketing, Sales, Operations, etc.
What You'll Need
Qualifications:
- 3+ years in a data engineer role supporting data science and analytics teams, preferably in a SaaS company or other environment with web-scale data (billions of rows) and cloud model deployments
- Prior programming experience in Python and SQL
- Track record of preparing and blending data for enterprise-wide BI tools: Tableau, Power BI (using DAX), Domo, etc.
- Experience with Apache Spark, Hadoop, or other parallel processing technologies preferred
- Experience with data visualization libraries, ER diagrams or tools preferred
- Strong understanding of data transformation techniques and cloud data platforms (preferably Azure Data Factory and Azure ML)
- High-level familiarity with machine learning techniques and data science libraries (Pandas, Scikit-learn, Keras, TensorFlow, etc.)
- Ability to thrive in a fast-paced remote-first startup environment
- Proactive and self-directed; excels at identifying opportunities to add value and contribute to the overall success of the team
- Analytical Mindset, Attention to Detail & Critical Thinking
- Time Management & Organizational Skills