DATA ENGINEER- DATA INGESTION FOCUS

You are looking for a hands-on Data Engineer who will be responsible for designing, building, and maintaining scalable data ingestion pipelines. Your main focus will be on ensuring the delivery of high-quality, reliable, and scalable data pipelines to support downstream analytics, machine learning, and business intelligence solutions. You will work with various internal and external sources to onboard structured and semi-structured data using Azure-native services like Data Factory, Azure Data Lake, Event Hubs, as well as tools like Databricks or Apache Spark for data ingestion and transformation. Your responsibilities will include developing metadata-driven ingestion frameworks, collaborating with source system owners to define data ingestion specifications, implementing monitoring/alerting on ingestion jobs, and embedding data quality, lineage, and governance principles into ingestion processes. You will also optimize ingestion processes for performance, reliability, and cloud cost efficiency, and support both batch and real-time ingestion needs, including streaming data pipelines where applicable. To qualify for this role, you should have at least 3 years of hands-on experience in data engineering, with a specific focus on data ingestion or integration. You should have hands-on experience with Azure Data Services or equivalent cloud-native tools, experience in Python (PySpark) for data processing tasks, and familiarity with ETL frameworks, orchestration tools, and working with API-based data ingestion. Knowledge of data quality and validation strategies, CI/CD practices, version control, and infrastructure-as-code are also required. Bonus qualifications include experience with SAP.,