Key Responsibilities:

Lead the design, development, and implementation of our big data solutions, ensuring they meet the business requirements and are scalable, reliable, and maintainable.
Collaborate with cross-functional teams, including data scientists, data analysts, and software engineers, to understand business needs and develop data-driven solutions.
Provide technical leadership and guidance to the team, including mentoring and coaching junior engineers, to ensure high-quality deliverables.
Evaluate and recommend new technologies and tools to improve the performance and efficiency of our big data solutions.
Develop and maintain the data architecture, ensuring data integrity, security, and compliance with data governance policies.
Design and implement data pipelines and ETL processes to ingest, transform, and store large volumes of data from various sources.
Optimize data storage and retrieval processes to improve performance and reduce costs.
Monitor and troubleshoot data pipelines and infrastructure to identify and resolve any issues in a timely manner.
Stay current with industry trends and advancements in big data technologies and tools, and incorporate them into our solutions as appropriate.

Qualifications:

Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
8+ years of experience in software development, with at least 5 years in big data technologies.
Strong proficiency in big data technologies, including Hadoop, Spark, Kafka, Hive, and SQL.
Experience with cloud-based data platforms, such as AWS, Azure, or Google Cloud.
Proven track record of designing and implementing data-driven solutions at scale.
Excellent leadership, communication, and problem-solving skills.
Ability to work in a fast-paced and dynamic environment, and manage multiple priorities and deadlines.
Experience with Agile methodologies and DevOps practices is a plus.

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