Data Engineer

• Design and implement comprehensive Lakehouse architecture solutions using technologies like Databricks, Snowflake, or equivalent platforms
• Build and maintain real-time and batch data processing systems using Apache Spark, Kafka, and similar technologies
• Architect scalable data pipelines that handle structured, semi-structured, and unstructured data to deliver AI ready data
• Develop data transformation workflows using tools like DBT, Airflow, or Databricks
• Lead the technical strategy for data lake and data warehouse integration, ensuring optimal performance and cost efficiency
• Implement data governance frameworks, including data quality monitoring, lineage tracking, data time travel and security protocols
• Implement centralized data catalog system and enhance data discovery using technologies like Elastic Search / Open Search
• Establish monitoring and alerting systems for data pipeline health using technologies like Apache Superset
• Drive adoption of modern data engineering best practices including Infrastructure as Code, CI/CD, and automated testing
• Collaborate with data scientists, analysts, and business stakeholders to translate requirements into robust technical solutions
• Mentor a team of 3-5 data engineers
• Foster a collaborative team culture focused on continuous learning and innovation

Senior Data Engineer – Lakehouse Architecture

Data Engineer, Level 2

Manager, Data Engineering – Data Collection