Lead Software Engineer

Key Responsibilities:

Migrate data pipelines from existing data acquisition framework to the new GDP data acquisition framework

Configure, develop and deliver data ingestion scripts for loading data into T1 data layer

Develop and manage ETL/ELT workflows, ensuring data quality, integrity, and reliability.

Integrate and automate data quality checks and validation processes within data pipelines.

Deploy and manage containerized applications using Docker and orchestrate workloads on Kubernetes.

Work with modern data lake and warehouse technologies such as Iceberg

Implement real time data streaming solutions using Kafka.

Orchestrate complex workflows using Airflow.

Integrate with data catalog and governance tools such as Datahub and Ranger.

Collaborate with cross functional teams to understand business requirements and deliver data solutions.

Ensure security, compliance, and best practices in data management and governance.

Key Skills Required:

Strong proficiency in Linux, Python, and Shell scripting.

Hands on experience with Docker, Kubernetes, and container orchestration.

Hands on experience with Minio and Azure Data Lake Storage (ADLS) using S3 protocols.

Experience with Apache Iceberg, Kafka, Airflow, Datahub, Trino, and Ranger.

Proficiency in Java for data engineering tasks.

Solid understanding of data modeling, data warehousing, and big data technologies.