Senior AWS Data Engineer

Join our cutting-edge Data Engineering team and design and develop modern data pipelines and platforms that support data-driven decision-making and AI-powered products.

Requirements

• Design, build, and optimize scalable data pipelines using PySpark, Databricks, and SQL on AWS cloud platforms.
• Collaborate with data analysts, data scientists, and business users to understand data requirements and ensure reliable, high-quality data delivery.
• Implement batch and streaming data ingestion frameworks from a variety of sources (structured, semi-structured, and unstructured data).
• Develop reusable, parameterized ETL/ELT components and data ingestion frameworks.
• Perform data transformation, cleansing, validation, and enrichment using Python and PySpark.
• Build and maintain data models, data marts, and logical/physical data structures that support BI, analytics, and AI initiatives.
• Apply best practices in software engineering, version control (Git), code reviews, and agile development processes.
• Ensure data pipelines are well-tested, monitored, and robust with proper logging and alerting mechanisms.
• Optimize performance of distributed data processing workflows and large datasets.
• Leverage AWS services (such as S3, Glue, Lambda, EMR, Redshift, Athena) for data orchestration and lakehouse architecture design.
• Participate in data governance practices and ensure compliance with data privacy, security, and quality standards.
• Contribute to documentation of processes, workflows, metadata, and lineage using tools such as Data Catalogs or Collibra (if applicable).
• Drive continuous improvement in engineering practices, tools, and automation to increase productivity and delivery quality.

Benefits

• Health insurance
• Dental insurance
• Vision insurance
• 401k plan
• Retirement plan
• Generous parental leave