AWS Data Engineer
Required skills
Experience in Data Engineering, including significant part on AWS. Solid skills in SQL and data-oriented programming. Mastery of at least several AWS data-oriented services (Glue, Redshift, S3, Athena, EMR, Kinesis...). Experience with PySpark or Spark for data processing. Knowledge of Data Lake and Data Warehouse architectures on AWS. Sensitivity to security, governance, and cost optimization.
Preferred skills
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Technologies
AWS (Glue, Lambda, Step Functions, Kinesis, S3, Athena, Redshift, EMR), Python, SQL, PySpark, Spark, Power BI, Tableau, Azure Data Factory, .Net, Java, Node.js.
Responsibilities
Design, develop, and maintain data pipelines on AWS. Integrate and transform data from various sources (SQL/NoSQL databases, APIs, ERP, CRM, flat files...). Use AWS services such as Glue, Lambda, Step Functions, Kinesis, S3, Athena, Redshift or EMR. Develop distributed and optimized processing with PySpark or Spark on AWS (EMR, Glue). Orchestrate and automate workflows with AWS Step Functions, Managed Airflow or equivalents. Implement data quality, consistency, and security controls (IAM, KMS, Lake Formation...). Optimize processing performance and reduce infrastructure costs. Document flows and ensure traceability. Collaborate with Data and IT teams to provide ready-to-use datasets. Participate in technological monitoring on AWS and cloud data solutions.
Seniority
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Domain
Data Intelligence, Cloud Native Development, Serverless Architecture
