Full-Time Data Engineer

Tasks

As a Data Engineer specializing in Google Cloud Platform (GCP), you will play a key role in designing, building, and maintaining our cloud-based data solutions. You will collaborate closely with our cross-functional teams to develop data pipelines, implement data ingestion processes, and ensure the reliability and scalability of our data infrastructure on GCP. The ideal candidate will have a strong background in data engineering, experience with GCP services, and a passion for leveraging cloud technologies to solve complex data challenges. 

Key Responsibilities:

• Design, develop, and maintain data pipelines and ETL processes on Google Cloud Platform (GCP) using services such as Cloud Dataflow, Apache Beam, or Google Cloud Composer.
• Implement scalable and reliable data ingestion mechanisms to collect, process, and store large volumes of structured and unstructured data.
• Optimize data storage and retrieval processes using GCP storage solutions such as BigQuery, Cloud Storage, and Cloud Bigtable.
• Collaborate with data scientists and analysts to support their data needs and ensure data accessibility, accuracy, and integrity.
• Monitor and troubleshoot data pipelines, identifying and resolving performance bottlenecks, data quality issues, and system failures.
• Implement data security and compliance measures to protect sensitive information and ensure regulatory compliance.
• Stay up-to-date with the latest developments in GCP services and cloud computing technologies, evaluating new tools and techniques to improve our data infrastructure.
• Provide technical guidance and mentorship to junior data engineers, fostering a culture of continuous learning and growth.

Requirements

• Bachelor's degree in Computer Science, Engineering, or related field.
• At least 7 years working as a Data Engineer
• Proven experience with a focus on Google Cloud Platform (GCP).
• In-depth knowledge of GCP services and products, including BigQuery, DBT (Data Build Tool), Cloud Storage, Dataflow, Pub/Sub, and Data Studio.
• Proficiency in programming languages such as Python, Java, or Scala for developing data pipelines and ETL processes.
• Strong understanding of data modeling, database design, and SQL query optimization.
• Experience with version control systems such as Git and CI/CD pipelines.
• Excellent problem-solving skills and attention to detail.
• Ability to work effectively in a fast-paced, collaborative environment with cross-functional teams.
• Google Cloud certification (e.g., Professional Data Engineer) is a plus.

Preferred Skills:

• Experience with other cloud platforms such as AWS or Azure.
• Knowledge of containerization technologies such as Docker and Kubernetes.
• Familiarity with streaming data processing frameworks such as Apache Kafka or Apache Flink.
• Understanding of machine learning concepts and frameworks.