Description

You will lead the migration of legacy SAS workloads to cloud and containerized platforms while designing scalable data architectures.

This role is on-site.

Responsibilities

• Convert existing SAS-based pipelines to PySpark for execution on distributed ecosystems.
• Design and implement scalable data pipelines that enforce data governance and quality policies.
• Develop high-level and detailed technical designs focusing on scalability, security, and performance.
• Collaborate with stakeholders to document dataflows and translate business requirements into technical solutions.
• Research and integrate open-source technologies and cloud-based components into the data architecture.

Required Skills

• 8+ years of experience in data engineering and large-scale data platform design.
• 3+ years of experience in a lead or architect role.
• 2+ years of experience in SAS coding.
• 2+ years of experience developing data solutions on AWS or GCP.
• Proficiency with Python, PySpark, and Scala.
• Hands-on experience with Docker and Kubernetes.
• Expert understanding of data warehousing, distributed systems, and cloud platforms (AWS, GCP).
• Experience with machine learning libraries.
• Strong skills in automation and technical documentation.

Preferred Skills

• Knowledge of Agile (Scrum) development methodologies.
• Experience with business process modeling tools.

Key Skills

Education

Any Gradute