Data Engineer

• Design, build, and maintain robust ETL/ELT pipelines to collect, process, and transform data from multiple internal and external sources.
• Develop and manage data models, schemas, and warehouse/lakehouse solutions (e.g., Snowflake, BigQuery, Redshift, Databricks).
• Ensure high standards of data quality, governance, and lineage across all systems.
• Implement workflow orchestration and automation using tools such as Airflow, dbt, or Dagster.
• Collaborate with analytics, product, and engineering teams to define and enforce data architecture best practices.
• Enable real-time and batch data processing pipelines using technologies like Kafka, Spark, or Flink.
• Optimize data storage, query performance, and cost efficiency across Sylndr’s data platforms.
• Champion modern data engineering principles — versioning, CI/CD, observability, and infrastructure-as-code.
• Work closely with the AI and Data Science teams to support model development and deployment pipelines.

Senior Data Engineer

Senior Data Engineer