Senior Data Engineer

Job Description:

We are seeking a highly skilled and experienced Senior Data Engineer to join our dynamic team. The ideal candidate will have a strong background in designing, building, and maintaining scalable data pipelines and platforms On Premise and Cloud Ecosystem (Microsoft Azure Preferrable), with hands-on expertise in modern data engineering tools and frameworks.

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 modelling, data warehousing, and big data technologies.

 Prior Experience:

·        Extensive background in building and maintaining data pipelines/ETL processes.

·        Experience in implementing and integrating data quality frameworks.

·        Extensive experience in working on migration projects moving from legacy data pipelines to modernized tech stack