Data Engineer – Data Pipelines & ETL

About the role

The Data Engineering team at Paramount is looking for a Data Engineer focused on building and maintaining scalable data pipelines and ETL/ELT processes. You will work on both batch and real‑time data systems that power analytics, machine learning and AI applications.

Key responsibilities

• Design, develop, and maintain scalable batch and streaming pipelines for large structured and unstructured datasets.
• Build robust ETL/ELT frameworks supporting analytics, BI, experimentation and ML use cases.
• Optimize pipelines for performance, reliability, scalability and cost efficiency, including CDC, incremental loads and event‑driven processing.
• Design dimensional and hybrid data models and reusable transformation layers for analytics and ML.
• Write production‑grade SQL and contribute to query optimization, indexing and partitioning.
• Develop modular data components and influence architectural decisions across streaming systems, data lakes and warehouses.
• Implement automated data validation, anomaly detection, monitoring, data lineage and metadata standards.
• Enforce governance, privacy, security and responsible AI data usage.

Required profile

• 2–4+ years of experience building and scaling ETL/ELT pipelines in production.
• Strong understanding of distributed data processing concepts.
• Experience with workflow orchestration tools such as Airflow or Composer.
• Expert‑level SQL skills for large‑scale transformation and analytics.
• Proven ability to design scalable warehouse schemas and ML‑ready data layers.

Required skills

• Airflow
• Composer
• SQL
• Data modeling
• ETL/ELT pipelines
• Change Data Capture (CDC)
• Incremental loads
• Event‑driven processing
• Data validation
• Anomaly detection
• Monitoring frameworks
• Data lineage
• Metadata management
• Cloud‑native architectures