Senior Data Engineer

Summary

Join Universal Audio's Digital Team and contribute to shaping the future of music creation by designing and implementing a scalable and secure data lake architecture. You will develop and optimize ETL/ELT pipelines, ensure data quality and governance, and optimize query performance in Amazon Redshift. This role involves collaborating with data analysts and the growth team to provide clean data models for business intelligence, automating infrastructure deployment using IaC tools, and monitoring data pipelines for high availability and reliability. You will also stay up-to-date with industry trends and introduce new tools and technologies to enhance efficiency.

Requirements

• Proficiency in SQL and experience optimizing queries in Amazon Redshift
• Experience with data lake architectures using AWS technologies such as S3, Glue, Athena, and Lake Formation
• Expertise in ETL/ELT pipeline development using tools such as Apache Airflow, DBT, or AWS Glue
• Strong programming skills in Python, Scala, or Java for data processing
• Experience with streaming data technologies such as Kafka or Kinesis
• Familiarity with cloud-based data infrastructure and IaC tools (Terraform, CloudFormation)
• Experience with CI/CD for data engineering workflows
• Knowledge of data governance, security, and compliance best practices
• Excellent problem-solving skills and ability to work in a fast-paced environment
• Bachelor's degree in Computer Science or related field
• 5+ years of experience in data engineering, with a strong focus on data lakes and data warehousing

Responsibilities

• Design and implement a scalable and secure data lake architecture to support structured, semi-structured, and unstructured data
• Develop and optimize ETL/ELT pipelines to ingest data from multiple sources into Amazon Redshift and other storage solutions
• Ensure data quality, governance, and compliance by implementing best practices for data validation, cataloging, and lineage tracking
• Optimize query performance in Amazon Redshift through advanced tuning techniques, indexing strategies, and partitioning
• Work closely with data analysts and growth team to provide clean, well-structured data models that support business intelligence
• Automate infrastructure deployment using Infrastructure-as-Code (IaC) tools such as Terraform or AWS CloudFormation
• Monitor and troubleshoot data pipelines, ensuring high availability and reliability of the data platform
• Stay up to date with industry trends and bring in new tools, technologies, and practices to improve efficiency

Preferred Qualifications

• Experience with vector databases for AI applications (e.g., Pinecone, Weaviate, FAISS)
• Proficiency in cloud-based AI services (AWS Sagemaker, Google Vertex AI, Azure ML)
• Experience with serverless AI data pipelines using AWS Lambda, Google Cloud Functions
• Familiarity with modern data stack tools like Snowflake, Databricks, or BigQuery

Benefits

• Profit sharing
• Medical/Dental/Vision
• 401K Safe Harbor Contribution
• Stock Options
• Flexible time-off (PTO/Sick Leave/Company Holiday Time-off)