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We are seeking a Senior Data Engineer to join our small, dynamic team focused on building modern data pipelines. This is an opportunity to work on greenfield projects without the burden of legacy system maintenance, creating robust data transformation solutions that power our internal systems.
Job Responsibility:
Design and develop new data pipelines using Spark to ingest data from multiple heterogeneous sources
Transform and standardize external data into our proprietary internal formats
Build scalable ETL/ELT processes that handle large-scale data processing
Collaborate on linked data initiatives, potentially working with JSON-LD and semantic data structures
Contribute to architectural decisions as a senior member of a small, agile team
Ensure data quality and reliability across all pipeline implementations
Requirements:
Extensive experience with Spark for distributed data processing
Proven track record building production-grade data ingestion pipelines
Experience with modern data engineering services (Databricks, AWS EMR, or similar)
Senior-level expertise with 5+ years in data engineering or software engineering roles
Ability to work independently and mentor team members in a small team environment
Nice to have:
Experience with Databricks platform and its ecosystem
Knowledge of Scala for Spark development
Knowledge of AWS data ecosystem
Familiarity with linked data concepts and JSON-LD format
What we offer:
Private medical insurance
National holidays off, even when falling on weekends