Kin + Carta is hiring a
Data Microstrategy Engineer

Summary

Join Kin + Carta's growing capabilities team as a Data Microstrategy Engineer and contribute to creating meaningful impact on large enterprise clients while maintaining scientific rigor and discipline.

Requirements

• Proven industry experience executing data engineering, analytics, and/or data science projects or Bachelors/Masters degree in quantitative studies including Engineering, Mathematics, Statistics, Computer Science or computation-intensive Sciences and Humanities
• Experience with the Microstrategy developer tool (as opposed to the web editor or workstation)
• Ability to use the Microstrategy object manager to migrate objects between dev, UAT, prod environments
• Understanding of the metadata architecture in MicroStrategy
• Ability to create batch job scripts and monitor cube performance
• Proficiency (can execute data ingestion to insight) in programmatic languages such as SQL, Python, and R

Responsibilities

• Analyze a collection of raw data sets to create a meaningful impact on large enterprise clients while maintaining a high degree of scientific rigor and discipline
• Engineer data pipelines and products to help stakeholders make and execute data-driven decisions
• Communicate analytical findings in an intuitive and visually compelling way
• Creating highly visual and interactive dashboards via Tableau, PowerBI, or custom web applications
• Conducting deep dive analysis and designing KPIs to help guide business decisions and measure success
• Engineering data infrastructure, software libraries, and APIs supporting BI and ML data pipelines
• Architecting cloud data platform components enabling the above
• Building and tracking project timelines, dependences, and risks
• Gathering stakeholder requirements and conducting technical due diligence toward designing pragmatic data-driven business solutions

Preferred Qualifications

• Proficiency in visualization/reporting tools such as Tableau and PowerBI or programmatic visualization library such as R ggplot2, Python matplotlib/seaborn/bokeh, Javascript D3
• Proficiency in big data environments and tools such as Spark, Hive, Impala, Pig, etc
• Proficiency with cloud architecture components (AWS, Azure, Google)
• Proficiency with data pipeline software such as Airflow, Luigi, or Prefect
• Ability to turn raw data and ambiguous business questions into distilled findings and recommendations for action
• Experience with statistical and machine learning libraries along with the ability to apply them appropriately to business problems
• Experience leading and managing technical data/analytics/machine learning projects