nclude optimizing data pipelines, ensuring data integrity and consistency, enhancing system resiliency where applicable, maintaining and improving data security, proactive alerting, and monitoring for data pipelines, and automating repetitive data-oriented tasks.
Responsibilities
Automate data tasks on Google Cloud Platform.
Work with data domain owners, data scientists and other stakeholders to that data is consumed effectively on Google Cloud Platform.
Design, build, secure and maintain data infrastructure, including data pipelines, databases, data warehouses, and data processing platforms on Google Cloud Platform.
Measure and monitor the quality of data on Google Cloud Platform data platforms.
Implement robust monitoring and alerting systems to proactively identify and resolve issues in data systems. Respond to incidents promptly to minimize downtime and data loss.
Develop automation scripts and tools to streamline data operations and make them scalable to ensure accommodate growing data volumes and user traffic.
Optimize data systems to ensure efficient data processing, reduce latency, and improve overall system performance.
Collaborate with data and infrastructure teams to forecast data growth and plan for future capacity requirements.
Ensure data security and compliance with data protection regulations. Implement best practices for data access controls and encryption.
Collaborate with data engineers, data scientists, and software engineers to understand data requirements, troubleshoot issues, and support data-driven initiatives.
Continuously assess and improve data infrastructure and data processes to enhance reliability, efficiency, and performance.
Maintain clear and up-to-date documentation related to data systems, configurations, and standard operating procedures.
Qualifications we seek in you!
Minimum Qualifications / Skills
Bachelor's or master's degree in computer science, Software Engineering, Data Science or related field, or equivalent practical experience
Preferred Qualifications/ Skills
Proficiency in data technologies, such as relational databases, data warehousing, big data platforms (e.g., Hadoop, Spark), data streaming (e.g., Kafka), and cloud services (e.g., AWS, Google Cloud Platform, Azure).
Strong programming skills in languages like Python (numpy, pandas, pyspark), Java (Core Java, Spark with Java, functional interface, lambda, java collections), or Scala, with experience in automation and scripting.
Experience with containerization and orchestration tools like Docker and Kubernetes is a plus.
Experience with data governance(data plex), data security, and compliance best practices on Google Cloud Platform.
Solid understanding of software development methodologies and best practices, including version control (e.g., Git) and CI/CD pipelines.
Strong background in cloud computing and data-Intensive applications and services, with a focus on Google Cloud Platform.
Experience with data quality assurance and testing on Google Cloud Platform.
Proficiency with Google Cloud Platform data services (BigQuery; Dataflow; Data Fusion; Dataproc; Cloud Composer; Pub/Sub; Google Cloud Storage).
Strong understanding of logging and monitoring using tools such as Cloud Logging, ELK Stack, AppDynamics, New Relic, Splunk, etc.
Knowledge of AI and ML tools is a plus.
Google Associate Cloud Engineer or Data Engineer certification is a plus.
Experience in data engineering or data science on Google Cloud Platform.
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