Key Responsibilities:

Design and implement highly scalable and reliable streaming data pipelines to support our growing data needs.
Collaborate with cross-functional teams to gather requirements and design data solutions that meet business needs.
Lead the development and deployment of data streaming architectures to enable real-time data processing and analysis.
Build and maintain data ingestion processes from various sources, with a focus on high-throughput and low-latency.
Monitor and troubleshoot data pipeline issues, ensuring timely resolution to minimize impact on business operations.
Develop and maintain data quality standards and implement data governance policies to ensure data accuracy and consistency.
Stay up-to-date with industry trends and best practices in streaming data technologies, and make recommendations for continuous improvement.
Mentor and provide guidance to junior team members, fostering a culture of technical excellence and collaboration.

Requirements:

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
At least 5 years of experience in a data engineering role, with a focus on streaming data.
Strong proficiency in Python, Java, or Scala, with experience in building data pipelines using tools such as Apache Kafka, Apache Spark, or AWS Kinesis.
Proven experience in designing and implementing highly available and scalable streaming data architectures.
In-depth understanding of database and data warehousing concepts, with experience working with SQL and NoSQL databases.
Experience with cloud computing platforms, such as AWS, Azure, or Google Cloud.
Excellent problem-solving and troubleshooting skills, with a strong attention to detail.
Proven experience in leading and mentoring a team of data engineers.
Strong communication skills, with the ability to effectively collaborate with cross-functional teams.

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