Remote Senior Data Analyst

Summary

Join Endpoint as a Senior Data Analyst to collaborate with cross-functional teams, build and maintain data solutions, and drive consensus. You will leverage your technical and analytical skills to manage stakeholder expectations and contribute significantly to the company's success.

Requirements

• 5+ years of Python expertise. Specializing in data engineering tasks like building, optimizing, and automating data pipelines
• Code quality & efficiency. Focus on writing clean, maintainable, and efficient Python code with strong practices in error handling, logging, and performance optimization for scalable solutions
• 5+ years of SQL experience. Advanced skills in SQL, including performance tuning
• Cloud platform proficiency. Extensive experience with AWS, GCP, or Azure, using Python to automate and optimize cloud infrastructure operations, including resource provisioning, security management, and cost control
• Data pipeline development. Proven ability to design and maintain scalable, high-performance data pipelines, utilizing tools like Prefect and dbt alongside Python
• Technical leadership. Ability to work closely with cross-functional teams to translate complex business needs into effective technical solutions, leveraging Python for impactful, data-driven decision-making
• Data orchestration. Experience in orchestrating ETL and reverse ETL processes using Python, with experience in tools like Prefect, Airflow, and Dagster to design complex data workflows
• Reliability & scalability focus. Commitment to ensuring the reliability and scalability of data systems through proactive monitoring, logging, and alerting, driven by Python solutions
• Data modeling & warehousing. Strong understanding of designing efficient data models and managing data warehouses, particularly on platforms like Snowflake, Big Query, and Redshift

Responsibilities

• Create, build, and manage highly scalable and efficient data pipelines for processing and integrating data from various internal and external sources
• Design and maintain data infrastructure to support high-volume data processing, ensuring reliability, scalability, and performance to contribute significantly to the company's success
• Collaborate closely with cross-functional teams, including Data Science, Product, and Engineering, to understand their data requirements and deliver robust solutions, emphasizing the need for solid communication and collaboration skills
• Conduct data profiling, cleansing, and transformation to ensure data accuracy, integrity, and availability across systems
• Identify opportunities to automate data processes and optimize existing pipelines to improve performance and reduce costs
• Develop and maintain detailed documentation for data pipelines, data models, and workflows, ensuring alignment with industry best practices and company standards
• Contribute to developing internal tools and frameworks that enhance data accessibility and usability across the organization
• Support data governance initiatives by ensuring compliance with data quality standards and contributing to data stewardship efforts to maintain the integrity and reliability of our data
• Stay abreast of the latest technologies and industry trends, continuously improve data engineering practices within the team, and cultivate a culture of continuous learning and growth
• Develop and implement optimized data models for data warehouses and data marts to meet the needs of analytics and reporting teams
• Drive operational excellence through a metrics-driven approach

Benefits

• Customizable benefits including Health, Dental, Vision, and 401K Match
• Flexible work options for specific roles
• Virtual and in-person team events
• Competitive compensation; Base pay is one part of your total compensation package in addition to annual bonus