Work closely with the Data Analysts to understand the business cases for analysis, challenges and data requirements
Work closely with Data Engineering team and serve as a business data expert, providing support in setting technical requirements, business acceptance testing and maintaining documentation
You will be overseeing existing data models, connections and automation for ZAGENO and Identifying opportunities for improving data reliability, efficiency and performance
As ZAGENO utilizes many 3rd-party data sources, you will be responsible for maintaining communication with the internal ZAGENO stakeholders
In your day-to-day work you will primarily use SQL, Python, GitHub, DBT, BigQuery, Databricks
Stay up-to-date on latest technologies and tools for data measurement and analytics.
Work with cross-functional stakeholders to understand their analytics needs to build efficient and scalable data solutions.
Work closely with the Abacus.ai and Data Engineering team for building AI/ML models
On this final point, professional growth, we are particularly focused on developing high potential, super smart people by adding to their technical skills - including AI; expanding their soft skills; and encouraging them to work with and learn from a wide array of colleagues of all experience levels.
About You:
2+ years of experience as an Analytics Engineer
Expertise in an object-oriented or functional language is required (we use Python)
Experience using BigQuery and DBT
Experience with Data Visualization tool - Tableau
Strong experience with Data Modeling
Experience working with Databricks using AWS Cloud
Strong SQL skills are required (we currently use Postgres, BigQuery, Databricks)
Expertise with cloud environments is a must (we are a GCP and AWS shop)
Experience with cloud data warehouses and distributed query engines is a plus
Keen attention to detail, proactive and curious
Ability to work with ambiguity and drive analytical solutions pragmatically to completion
Proven record of designing and developing systems with desired SLAs and data quality metrics
Experience with Machine Learning MLOPs is a big plus
Experience working with Data Observability solutions (Metaplane, Acceldata, etc.)
Technical understanding of the importance of performance measures and their relation to business objectives
A global team player, energized by collaborating and leading across cultures and geographies.
