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.