Senior Analytics Engineer

$141,170 - $146,170/Yr

MongoDB - New York, NY

Full-time - Mid Level

Remote - New York, NY

Professional, Scientific, and Technical Services

About the position

The Senior Analytics Engineer at MongoDB, Inc. is responsible for collaborating with stakeholders to gather requirements and develop data solutions. This role involves writing data pipelines, designing datasets, and deploying code in production environments. The engineer will also debug data quality issues, document datasets, and present new datasets to users. Additionally, the position includes performing code reviews, generating clarity around ambiguous problems, and assisting in recruitment processes.

Responsibilities

• Work with stakeholders to gather requirements and communicate timelines.
• Write data pipelines in SQL and Python.
• Design new datasets and data models for analytics.
• Use Kubernetes and GitHub to deploy code in production environments.
• Debug data quality issues impacting pipelines.
• Document datasets in internal knowledge bases.
• Present demos on new datasets to potential users.
• Perform code reviews for other analytics engineers and analysts.
• Work independently to clarify ambiguous problems and develop data solutions.
• Identify and address technical architecture deficiencies.
• Develop new tools and systems to enhance Analytics Engineering workflow.
• Maintain documentation of work and knowledge through JIRA, Alation, Google Docs.
• Evangelize Analytics Engineering solutions and best practices through demos and meetings.
• Provide feedback on standard operating procedures and service-level agreements.
• Assist in recruitment and interview processes.

Requirements

• Bachelor's degree or foreign degree equivalent in Computer Science, Engineering, Analytics, or related field and four (4) years of experience in analytics engineering or related role.
• Alternatively, a master's degree or foreign degree equivalent in the same fields and two (2) years of experience.
• Proficiency in SQL for analytics and data pipelining.
• Experience with Python and Pandas.
• Knowledge of Airflow for data transformations.
• Understanding of data pipelining, including performant and idempotent code, backfills, and schema evolution.
• Experience with PySpark for parallel computing on large datasets.
• Ability to manage automated task orchestration in Airflow.
• Familiarity with Bash/Shell.

Benefits

• Work from home 3-4 days a week
• Flexible in-office work 1-2 days a week
• Competitive salary range of $141,170/yr - $146,170/yr