Description

Key Responsibilities 

Develop and maintain data pipelines, transformations, reports, models, or platform components as required by the role. 

Translate source-to-target and business requirements into validated technical data solutions. 

Implement data quality checks, access controls, monitoring, and failure-recovery procedures. 

Tune SQL, processing jobs, models, dashboards, or platform resources for performance and cost. 

Document data definitions, lineage, operational procedures, and technical decisions. 

Required Qualifications 

Experience Required: typically 4+ years in a related professional role; exact threshold must match the approved requisition. 

Practical experience with the role-specific technology stack: SQL, Python/Scala, ETL/ELT, data modeling, Spark or equivalent processing, orchestration, and cloud data platforms. 

Professional experience in data engineering, analytics, data management, or the platform area relevant to this role. 

Strong SQL skills and practical experience with the data technologies identified for the position. 

Understanding of data modeling, ETL/ELT, data validation, and integration patterns. 

Experience with data quality, security, access controls, and production support. 

Ability to translate business requirements into accurate and maintainable data solutions. 

Strong analytical, documentation, and stakeholder communication skills. 

Preferred Qualifications 

Additional hands-on depth in SQL, Python/Scala, ETL/ELT, data modeling, Spark or equivalent processing, orchestration, and cloud data platforms. 

Experience with cloud services, automation, and modern delivery practices relevant to the project. 

Familiarity with secure development, accessibility, governance, or regulatory requirements where applicable. 

Relevant professional certifications or advanced training in the role’s technology area

Key Skills

Education

Bachelor's degree