Data Engineer

Key Skills

Java Programming, Python Programming, SQL, R Programming

Job Description

We are presently looking for a Data Engineer which is part of our Gracenote Content operations team. The Content operations team is responsible for the ingestion and enrichment of our metadata for use by our clients. This role is to assist in the organization’s journey to leverage our vast metadata content and harmonize data both on-prem and in the cloud. Collaborating with the operational teams to measure and improve data quality, access and combine datasets for use in quality projects, is paramount to succeed in his role. Familiarity with data integration, AWS cloud services, analytical systems, data harmonization, and data automation are key in this role.

 RESPONSIBILITIES:

• Works with the Quality Office and cross-functional teams to identify data quality issues and implement systems to make them visible with data quality metrics and threshold
• Responsible for building data pipelines and data integration projects to measure data quality
• Build and optimize data queries from multiple relational databases, data warehouses, data lakes for various analyses and requests
• Ability to translate raw data into visualizations to be understood by multiple (technical and non-technical stakeholders) or in data staging.
• Support the team to productionize their workflows and analysis, while building tools and infrastructure to improve their speed and effectiveness
• Collaborate in the Cloud Journey for Content Operations as the organization moves from on-prem (Oracle, MySQL, Postgres, etc) landscapes to cloud.

QUALIFICATIONS:

• Strong hands-on experience with SQL, data warehousing, dashboarding and reporting, involving large datasets and multiple data sources
• 2+ years experience working as an Engineer on data-intensive applications, architecting large-scale production systems
• Extensive experience with scripting languages (such as Python) with a track record of clean, efficient code design
• Experience in data integration of multiple databases (relational data stores - RDS, Aurora; SQL data stores - Postgres, Oracle, MySQL; data warehouses - Redshift, Snowflake)
• AWS knowledge and experience is a plus, specifically EMR, IAM, EC2, S3, Kinesis, Lambda, Glue, S3, Terraform cloud formation, autoscaling.
• Sound understanding of SQL fundamentals and past experience with data warehousing, data modeling and schema design
• Bachelor or Master in Computer Science, or equivalent work experience

ABOUT THE TEAM

 The team measure and improve data quality, we need to move massive quantities of data and report on them over time using dashboards that are accessible and clear to everybody.