Platform Engineer for Data Engineer

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Platform Engineer with expertise in the AWS data stack to join our dynamic team. The ideal candidate will be responsible for designing, building, and maintaining modern scalable and robust data platforms that support our data-driven initiatives (e.g. Data mesh, data products). This role collaborates with data scientists, analysts, and other stakeholders to ensure our data infrastructure is optimized for performance and aligned with business goals.

Key Responsibilities:

• Design, implement, and manage data solutions using AWS data services such as Amazon Redshift, Amazon EMR, Amazon Kinesis, AWS Glue, AWS Lake Formation, and Amazon Athena.
• Ensure the architecture and design of the data platform meet business requirements for reliability, availability, and scalability.
• Automate infrastructure provisioning, deployment, and scaling using AWS CloudFormation, Terraform, or other infrastructure as code tools.
• Develop and implement data engineering best practices, including continuous integration and delivery (CI/CD) pipelines for data platforms.
• Monitor, troubleshoot, and optimize data platforms for performance issues.
• Collaborate with security teams to implement and maintain data governance, compliance, and security policies.
• Provide technical guidance and support to other team members and stakeholders regarding data platform capabilities and best practices.
• Stay current with new AWS services and other data technologies, evaluating their applicability to our goals and integrating them as appropriate.
• Participate in on-call rotations for supporting critical data platform operations.

Qualifications:

• AWS certifications related to data services or solutions architecture.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• At least 3 years of experience working with AWS data services and infrastructure.
• Proficiency in scripting languages such as Python, Shell, or similar for automation tasks.
• Experience with infrastructure as code (IaC) tools such as AWS CloudFormation or Terraform.
• Strong knowledge of SQL and experience in optimizing complex queries.
• Familiarity with data pipeline and workflow management tools.
• Understanding of the principles of data warehousing, ETL processes, and data modeling.
• Proficient in implementing security and compliance standards within AWS.
• Excellent problem-solving skills and ability to work under pressure.
• Experience with DevOps practices and tools (e.g., Jenkins, Git).
• Knowledge of containerization and orchestration services (e.g., Docker, Kubernetes).
• Prior experience with big data technologies (e.g., Hadoop, Spark).
• Experience working in an Agile/Scrum development process.

Seniority level

• Seniority levelMid-Senior level

Employment type

• Employment typeFull-time

Job function

• Job functionFinance

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