01Responsibilities
BI: Develop modern data architectural approaches for business intelligence reporting and analytics, including that for machine learning models and data science, ensuring effectiveness, scalability, and reliability.
ETL: Develop modern data architectural approaches for ETL processes.
Gather and build canned and ad hoc reports, and dashboards using reporting and visualization tools. Provide support and education to the business units on published data models.
Collaborate with other data engineers, data scientists, and product managers to implement a shared technical vision
Technical Writing, including documentation of analyses, justification of insights, PowerPoint presentations of conclusions, technical proposals, etc.
Skills Required:
5+ years of software development and architecture knowledge
2+ years working with Python or other high-level development language.
5+ years working in production software development environments.
3+ years of development and knowledge of Data Warehousing principles, ELT / ETL processes and dimensional modeling concepts.
Experience with Cloud-based data management services.
Experience with Data wrangling, transformations, filtering, etc.
Strong SQL skills.
Advanced data aggregation and modeling skills, using the latest techniques and best practices for query tuning (i.e., partitioning, clustering, nesting, optimizing join patterns, and analytics-window functions).
Strong Expertise in Cloud-based Services [ GCP and or AWS] for data management [GCS, Big Query and or RedShift, S3) and workflow orchestration processing. [ex: Airflow, Dataflow, GCP Composer, AWS Glue, etc.]
Hands-on experience with building reports and dashboards
Experience with CI/CD pipeline integrations and documentation.
Highly analytical, data-driven thinker.
Self-starter, able to work autonomously with little oversight/guidance. .
