Data Engineer
Core
Design and build scalable, high-performance data pipelines for extracting, transforming, and loading data into cloud data lakes and warehouses; build and deploy AI/ML models integrated into data pipelines.
Role type
Senior Data Engineer (Cloud & AI/ML)
Builds
Cloud data lakes, data lakehouses, secure data warehouses, and AI/ML-integrated data pipelines
Domain
Cloud data engineering, Big Data, AI/ML integration
Deliverable
production ML models
Required skills
Data pipeline development, Data warehousing concepts, ETL/ELT workflows, Performance optimization, Cross-functional collaboration, Big data technologies
Preferred skills
Azure Databricks, Apache Spark, Azure Data Lake Storage, Azure Data Factory, Databricks ML, AWS Glue, AWS Lambda, Amazon Kinesis, Amazon EMR, Amazon Athena, Amazon DynamoDB, Amazon CloudWatch, Amazon SNS, AWS Step Functions, AWS Redshift, AWS RDS, Hadoop, AWS S3, Python, Java, Scala, PySpark, Azure Data Engineer Associate certification, Databricks Certified Data Engineer Professional certification
Technologies
Azure Databricks, Apache Spark, Azure Data Lake Storage, Azure Data Factory, Databricks ML, Azure ML, AWS Glue, AWS Lambda, Amazon Kinesis, Amazon EMR, Amazon Athena, Amazon DynamoDB, Amazon CloudWatch, Amazon SNS, AWS Step Functions, AWS Redshift, AWS RDS, Hadoop, AWS S3, Python, Java, Scala, PySpark
Responsibilities
Design and build scalable, high-performance data pipelines; Develop and maintain secure data warehouses and data lakehouses; Implement ETL and ELT workflows; Build and deploy AI/ML models; Monitor and optimize data pipelines and infrastructure; Collaborate with business analysts, data scientists, and DevOps engineers
Seniority
Senior, hands-on IC
