Scribd is hiring a
Principal Data Engineer

Summary

The job is for a Data Architect at Scribd where the employee will lead the design and development of data architecture and guide Scribd's data strategy. They will work with various teams to design cohesive data models, database schemas, and data storage solutions. The role requires 7+ years of experience in data strategy, data architecture, modeling, solution design, data engineering, or a similar role, proficiency in SQL, and hands-on experience with data lake technologies, data storage formats, query engines, and ETL processes.

Requirements

• 7+ years of experience in data strategy, data architecture, modeling, solution design, data engineering, or a similar role
• Hands-on experience and knowledge of data lake technologies (Databricks, Snowflake, etc), data storage formats (Parquet, Avro etc.)  and query engines (Athena,Presto etc.), data schemas, optimization of queries and associated concepts for building optimized solutions at scale
• Strong understanding of distributed systems, Restful APIs and data consumption patterns
• Proficiency in data modeling, ETL processes, and real-time and batch analytics frameworks
• Proficient with at least one dialect of SQL
• Hands-on experience in Scala or Python

Responsibilities

• Lead the design and development of a robust data architecture that guides data modeling, integration, processing, and delivery standards enabling modern data product development at Scribd
• Serve as a data and analytics solution architect, leading architecture initiatives encompassing data warehousing, data pipeline development, data integrations, and data modeling
• Shape Scribd’s data strategy, guiding stakeholders in how they consume and act on data

Preferred Qualifications

• Experience and working knowledge of streaming platforms, typically based around Kafka
• Strong grasp of AWS data platform services and their strengths/weaknesses
• Hands on experience in implementing data pipelines for data ingestion and transformation to support analytics and ML pipelines
• Strong experience communicating asynchronously using collaboration tools like Jira, Slack, etc
• Experience using automation and CI/CD tooling like Git, GitHub,Docker,Jenkins, Terraform, etc
• Experience developing standards for database design and implementation of various strategic data architecture initiatives around data quality, data management policies/standards, data governance, privacy and metadata management
• Working experience integrating with BI frameworks like Qlik, ThoughtSpot, Looker, Tableau, etc

Benefits

• Base pay is one part of your total compensation package and is determined within a range. The salary ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location
• The position is eligible for a competitive equity ownership, and a comprehensive and generous benefits package