Manager - Information Technology, Data Engineering

Job highlights

• Design,build and maintain real-time and batch data pipelines using Python,PySpark,and AWS services.

• Design, build and maintain real-time and batch data pipelines using Python, PySpark, and AWS services.

• Architect and manage cloud infrastructure with a focus on scalability, cost-efficiency, and performance (AWS Glue, Lambda, S3, Athena).

• Implement and optimize ETL/ELT workflows, ensuring data quality and reliability.

• Integrate data from diverse sources, including APIs (REST/GraphQL), into centralized data warehouses.

• Work with streaming technologies like Kafka or Amazon Kinesis to handle high-throughput, low-latency data ingestion.

• Lead data modeling efforts and contribute to the design of enterprise data warehouses and data lakes.

• Collaborate with product, engineering, and analytics teams to identify data needs and translate them into scalable solutions.

• Mentor junior data engineers and contribute to best practices, code reviews, and process improvements.

• Drive innovation by evaluating and implementing emerging tools such as Airflow, dbt, Docker, Kubernetes, or MLOps platforms.