Data Engineer

Qualification

2 years of experience as a Data Engineer or similar role. Strong proficiency in Python or other programming languages relevant to data engineering. Any additional experience with any of the following: Hands-on experience with data pipeline orchestration tools (e.g., Apache Airflow, dbt, Prefect, Dagster). Solid understanding of cloud platforms (AWS strongly preferred; GCP or Azure experience also considered). Expertise in SQL and familiarity with relational and columnar databases (e.g., PostgreSQL, Snowflake, BigQuery). Knowledge of big data processing frameworks (e.g., Apache Spark, Databricks, or Apache Kafka). Familiarity with machine learning workflows and experience implementing MLOps tools (e.g., Amazon SageMaker, MLflow, or Kubeflow) in production environments. Strong troubleshooting skills and experience monitoring data pipelines and system health using tools like Amazon CloudWatch, Datadog, or Great Expectations. Excellent communication skills and a collaborative mindset, with a focus on documentation and best practices. Preferred