GCP Data Engineer - Python / SQL

About Company : They balance innovation with an open, friendly culture and the backing of a long-established parent company, known for its ethical reputation.

We guide customers from whats now to whats next by unlocking the value of their data and applications to solve their digital challenges, achieving outcomes that benefit both business and society.

Job Title : GCP Data Engineer.

Location : Hyderabad, Pune.

Work Mode : Hybrid.

Experience : 5+ years (4 years Relevant).

Job Type : Contract to hire (C2H).

Notice Period : Immediate joiners.

Mandatory Skills : GCPBig Query, Dataproc, Airflow, Pyspark, Python, SQL.

We are looking for a highly skilled Data Engineers with 5 to 9 years of experience in data engineering specializing in PySpark, Python, GCP, IAM CS DataProc BigQuery SQL Airflow and building data pipelines Handling TerabyteScale Data Processing The ideal candidate will have a strong background in designing developing and maintaining scalable data pipelines and architectures.

Key Responsibilities :

• Design develop and maintain scalable data pipelines using PySpark, Python, GCP, and Airflow.
• Implement data processing workflows and ETL processes to extract transform and load data from various sources into data lakes and data warehouses.
• Manage and optimize data storage solutions using GCP services.
• TerabyteScale Data Processing Developed and optimized PySpark code to handle terabytes of data efficiently Implemented performance tuning techniques to reduce processing time and improve resource utilization.
• Data Lake Implementation Built a scalable data lake on GCP CS to store and manage structured and unstructured data.
• Data Quality Framework Developed a data quality framework using PySpark and GCP to perform automated data validation and anomaly detection Improved data accuracy and reliability for downstream analytics.
• Collaborate with data scientists analysts and other stakeholders to understand data requirements and deliver highquality data solutions.
• Perform data quality checks and validation to ensure data accuracy and consistency.
• Monitor and troubleshoot data pipelines to ensure smooth and efficient data processing.
• Stay updated with the latest industry trends and technologies in data.

(ref : hirist.tech)