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Senior, specialized data engineering stack reduces candidate density.
Core data engineering skills (Python, SQL, Snowflake, Kafka) are broadly transferable across industries.
Explicit 8+ years and mandatory Snowflake, Kafka, Spark, Python/DBT, cloud indicate strict technical filters.
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Design, develop, and operate data warehouse, data platforms, and data pipelines using ETL/ELT processes.
Create and implement complex analytical data models and build reporting solutions to support business analytics requirements.
Provide operational post-production support following DevOps principles and collaborate closely with business and functional teams.
8+ years of experience in data engineering with strong knowledge in Python and DBT.
Experience with Data Warehousing technologies such as Snowflake or BigQuery and strong SQL skills including query writing and optimization.
Experience processing batch and streaming data at scale using big data technologies like Apache Kafka, Spark, or Flink.
Bachelor’s degree in Computer Science, Electrical Engineering, or related Engineering disciplines.
Experienced in working with cloud environments such as AWS or GCP and familiar with cloud computing concepts.
Demonstrates a DevOps-oriented operating style, including experience with CI/CD pipelines and post-deployment operational support.
Capable of working independently and effectively on distributed, remote agile teams with strong communication skills.