New Relic is looking for a Senior Data Engineer to help drive deep business understanding and leverage data to identify critical business checks, anomalies, and define key business rules. This role is crucial for enabling both internal teams and New Relic customers to gain trusted and actionable insights from data, driving strategic business outcomes.
Requirements
- Proficiency in SQL for data extraction, manipulation, and analysis.
- Experience with data visualization tools (e.g., Tableau, Looker, Power BI) for creating impactful dashboards and reports.
- Experience working with ML/AI teams on defining data requirements for model development and deployment.
- Understanding of data pipeline concepts and ETL/ELT processes.
- Exposure to cloud data platforms (e.g., Snowflake, BigQuery, Redshift).
- Experience with statistical analysis or data modeling techniques.
- Familiarity with data governance principles and best practices.
Responsibilities
- Collaborate closely with ML and Data Engineering teams to translate business requirements into technical specifications for data pipelines, models, and analytical solutions.
- Develop and implement robust data validation and quality checks to ensure the accuracy and reliability of business-critical data.
- Design and build insightful dashboards and reports that provide business stakeholders with actionable insights and monitor key performance indicators.
- Lead incident response for data quality or business rule issues, conducting root cause analysis and implementing preventative measures.
- Translate complex business problems into data analysis requirements.
- Identify anomalies, trends, and patterns in large datasets.
- Contribute to internal and customer-facing data product strategy, focusing on business value and user adoption.
Other
- 5+ years of experience in data analysis, with a strong emphasis on business analysis and defining business rules.
- Proven ability to deeply understand business processes and translate complex business problems into data analysis requirements.
- Strong analytical skills with experience in identifying anomalies, trends, and patterns in large datasets.
- Excellent communication and interpersonal skills, with the ability to effectively collaborate with business stakeholders, ML engineers, and data engineers.
- Ability to think productively and partner with business and AI teams to drive data-driven solutions.
