Responsibilities
- Design, build, and maintain scalable data platform pipelines and infrastructure to support large-scale ingestion, processing, and analytics across the business.
- Develop reusable frameworks for data ingestion, transformation, cleansing, and data quality, ensuring reliable flow into data lakes and warehouses.
- Partner closely with cross-functional teams (Operations, Sales, Product) to deliver data models and insights that support business strategy and decision-making.
- Qualifications
- 6–10 years of experience in data engineering or data-centric software engineering with strong expertise in Python and SQL.
- Deep experience with data platforms and tools including orchestration (Airflow, Prefect, Dagster), cloud environments (AWS/GCP/Azure), and databases (Snowflake, Databricks, PostgreSQL, MongoDB).
- Strong understanding of ELT/ETL frameworks (dbt, etc.), distributed/streaming systems (Kafka, Spark, Flink), and infrastructure-as-code tools (Terraform or CloudFormation), with excellent communication and collaboration skills.
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