Data Engineer - Google Cloud Platform (3-6 yrs)

About the Job :

We are looking for a talented and driven GCP Data Engineer with strong SQL skills to join our growing team.

You will be instrumental in building and maintaining our data infrastructure on Google Cloud Platform (GCP), enabling data-driven insights and informed business decisions.

This role offers the opportunity to work on diverse global projects, exposing you to a wide range of technologies and challenges.

Responsibilities :

- Design, develop, and maintain robust and scalable data pipelines using GCP services like Dataflow, Dataproc, BigQuery, Cloud Storage, and Pub/Sub.

- Write complex and efficient SQL queries for data extraction, transformation, and loading (ETL) processes.

- Optimize SQL queries for performance and scalability.

- Design and implement data warehousing solutions on GCP, adhering to best practices for data modeling and schema design.

- Perform data profiling, cleansing, and validation to ensure data quality and integrity.

- Collaborate with data scientists and business analysts to understand data requirements and translate them into technical solutions.

- Implement data governance and security measures to protect sensitive data.

- Monitor and troubleshoot data pipelines, identifying and resolving performance bottlenecks and data quality issues.

- Automate data processing tasks and workflows using scripting languages (e., Python) and workflow orchestration tools (e., Airflow).

- Participate in code reviews and contribute to the improvement of our data engineering practices.

- Stay up-to-date with the latest GCP services and data engineering trends.

- Contribute to the documentation of data pipelines and data warehousing solutions.

- Participate in agile development processes.

- Implement data migration strategies from legacy systems to GCP.

Qualifications :

- 3+ years of experience as a Data Engineer.

- Proven experience with Google Cloud Platform (GCP) services, including Dataflow, Dataproc, BigQuery, Cloud Storage, and Pub/Sub.

- Expert-level SQL skills, including experience with complex queries, performance tuning, and database design.

- Strong understanding of relational databases (e. MySQL, SQL Server, Oracle) and data warehousing concepts.

- Experience with data modeling and schema design.

- Proficiency in at least one scripting language (e. , Python).

- Experience with data pipeline orchestration tools (e, Airflow) is a plus.

- Strong problem-solving and analytical skills, with the ability to analyze and interpret complex data.

- Excellent communication and collaboration skills.

- Experience with data mining techniques is a plus.

- Experience with data visualization tools (e., Looker, Tableau) is a plus