Senior Data engineer

This role will be responsible for driving data platform architecture, data engineering, infrastructure, and open-source technology implementation while working closely with Business Users, Management, Architects, Data Scientists, and Engineering teams.

Responsibilities

• Lead the design, implementation, modernization, and operation of enterprise-scale Data Platform and Data Engineering solutions.
• Design and manage scalable ETL/ELT, data pipelines, data integration, and workflow orchestration using technologies such as Python, SQL, PySpark, and Apache Airflow.
• Design and implement Data Warehouse, Data Lake, Lakehouse, Data Modeling, Data Governance, and real-time data solutions using technologies such as Kafka and Spark.
• Lead the deployment and management of data platform infrastructure across on-premise, cloud, or hybrid environments, including Kubernetes, Docker, CI/CD, Terraform/Ansible, HA, and DR.
• Evaluate and implement Open Source Data Platform technologies and support data environments for AI/ML and Generative AI use cases, including MLOps, LLM, RAG, and Vector Databases.
• Lead and mentor technical teams while collaborating with Business Users, Management, Architects, Data Scientists, and other stakeholders to deliver secure, scalable, and reliable data solutions.

Job Specification

• Bachelor’s or Master’s Degree in Computer Science, IT, Data Science, Engineering, Mathematics, or related fields.
• 8+ years of experience in Data Engineering, Data Platform, Big Data, or related fields.
• Proven experience leading enterprise-scale Data Platform projects.
• Strong hands-on experience with Python, JavaScript/Node.js, SQL, PostgreSQL, PySpark, and Airflow.
• Strong technical leadership, problem-solving, and stakeholder management skills.