Lead Data Engineer

This position covers data engineering, data warehousing, and cloud platforms. This role will involve leading the design and development of robust data pipelines, streaming ingestion frameworks, and scalable data architectures to support our data-driven initiatives.

Responsibilities:

• Lead the design, development, and maintenance of scalable data pipelines, ETL/ELT processes, and data models.
• Focus on Kafka, HDFS, HBase, Parquet, Spark, and Flink to ensure efficient data ingestion, storage, and processing.
• Build and manage data ingestion frameworks using big data technologies, ensuring high efficiency and reliability.
• Develop and optimize data storage solutions, including data warehousing, data lakes, and NoSQL databases on cloud platforms such as AWS.
• Work with various data formats, including Parquet, Avro, and others, to ensure efficient data processing and storage.
• Mentor and provide technical leadership to junior data engineers, fostering a culture of continuous learning and improvement.

Requirements:

• Bachelor’s degree in Computer Science, Engineering, or a related field; Master’s degree preferred.
• 5+ years of proven experience as a Data Engineer or in a similar role, with a strong focus on data warehousing, ETL/ELT processes, and data modeling.
• Proficiency in programming languages such as Python.
• Hands-on experience with big data technologies such as specifically Spark.
• Experience with the AWS cloud platforms .
• Strong SQL skills and experience working with both relational and NoSQL databases.
• Familiarity with data visualization tools such as Tableau, Power BI, or Looker.
• Experience with building and managing data pipelines in a multi-cloud environment.
• Experience in mentoring or leading a team of data engineers.