Google Cloud Platform Data Engineer

Job Description:
10 years of Python and SQL skills.

Key Responsibilities:
Advanced Data Analysis:
Perform deep-dive data analysis using SQL, Python, and R to uncover trends, patterns, and actionable insights.
Collaborate with stakeholders to translate business questions into analytical solutions.
ETL & Dashboard Development:
Design, build, and maintain automated ETL pipelines on Google Cloud Platform using tools like Dataflow, BigQuery, and Cloud Composer.
Develop and deploy real-time dashboards using Looker, Data Studio, or other BI tools to support data-driven decision-making.
Workflow Optimization:
Identify and implement opportunities to streamline data workflows across cross-functional teams.
Drive process improvements and automation to enhance data accessibility and reliability.
High-Impact Delivery:
Thrive in a fast-paced, high-impact environment, managing multiple priorities and delivering results under tight deadlines.
Communicate findings and recommendations clearly to both technical and non-technical audiences.
Required Skills & Qualifications:
Proficiency in SQL for complex data querying and transformation.
Intermediate experience with Python and R for data manipulation and statistical analysis.
Hands-on experience with Google Cloud Platform services such as BigQuery, Cloud Storage, Dataflow, Pub/Sub, and Cloud Functions.
Experience building automated ETL pipelines and working with streaming data.
Familiarity with dashboarding tools like Looker, Tableau, or Google Data Studio.
Strong problem-solving skills and ability to work independently and collaboratively.
Excellent communication and stakeholder management skills.
Preferred Qualifications:
Google Cloud Platform certification (e.g., Professional Data Engineer).
Experience with CI/CD pipelines and infrastructure as code (e.g., Terraform).
Background in data science or machine learning is a plus.