GCP Data Engineer

Job Summary

Proficiency in programming languages such as Python and SQL. Looking for Google Cloud Platform skill sets - Google Dataflow, Google Dataform, Google SQL (BigQuery). Experience with data engineering tools and technologies (e.g., Apache Spark, Hadoop, Airflow, Kafka). Knowledge of data modeling techniques and database technologies (SQL and NoSQL). Good problem-solving analytical and debugging skills with collaborative approach to finding solutions. Strong communication and collaboration skills, with the ability to effectively interact with cross-functional team members. Ability to work independently on assigned tasks and contribute actively as a valued member of a self-organizing team.

Responsibilities

• Develop and support defined data pipelines or ETL processes with limited oversight.
• Participate in agile ceremonies to contribute to effective sprint planning, transparent communication, and the successful delivery of sprint goals.
• Test own work with limited oversight to ensure accuracy, reliability, and performance.
• Work closely with product owners and other cross-functional team members to deeply understand user stories and deliver valuable solutions in alignment with sprint goals.
• Contribute to data modeling, data architecture, and data governance initiatives.
• Implement data quality checks and monitoring for data pipelines.
• Collaborate with data scientists, analysts, and other stakeholders to understand requirements and deliver solutions.
• Contribute to the continuous improvement of development processes and tools through active participation in team retrospectives and feedback loops.

Requirements

• Bachelor's degree in Computer Science, Engineering, Data Science, Statistics, or a related field (or equivalent practical experience).
• Minimum of 2+ years of experience in data engineering.

Skills

• Python
• SQL
• Google Cloud Platform skill sets: Google Dataflow, Google Dataform, Google SQL (BigQuery)
• data engineering tools and technologies (e.g., Apache Spark, Hadoop, Airflow, Kafka)
• data modeling techniques and database technologies (SQL and NoSQL)
• problem-solving, analytical and debugging skills
• strong communication and collaboration skills
• ETL

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