Gcp data engineer

3 weeks ago

Delhi, India NASTech, IT Full time
Job Title:  GCP Data Engineer
About the Role: We are seeking an experienced  GCP Data Engineer  to join our dynamic data engineering team. As a Data Engineer, you will design, develop, and maintain data pipelines on Google Cloud Platform (GCP) to support large-scale data analytics and machine learning initiatives. The ideal candidate will have a strong background in working with  Big Query ,  Python , and  Databricks.
Key Responsibilities: Design and Build Data Pipelines:  Develop scalable and efficient data pipelines using  GCP services  such as  Big Query ,  Cloud Dataflow ,  Cloud Storage , and  Pub/Sub.
Big Query Optimization:  Optimize queries, build materialized views, and ensure the efficiency and performance of large datasets in  Big Query.
Data Modeling and ETL:  Create and maintain  ETL (Extract, Transform, Load)  processes, transforming raw data into structured, easily accessible formats for analytics.
Automation and Scripting:  Write Python scripts to automate data workflows, integrate data sources, and manage metadata for data governance.
Databricks Integration:  Work with  Databricks  for data processing, including the use of  Apache Spark  for batch and stream processing.
Collaboration:  Collaborate with Data Scientists, Analysts, and other stakeholders to understand data requirements and provide effective solutions.
Data Quality and Governance:  Ensure data integrity, quality, and security by following best practices for data governance, monitoring, and logging.
Required Skills and Qualifications: Experience with GCP Services:  Hands-on experience with  Google Cloud Platform  tools, especially  Big Query ,  Dataflow ,  Pub/Sub ,  Cloud Storage ,  Cloud Functions , and  Cloud Composer.
Proficiency in Python:  Strong Python programming skills, especially for data engineering, data transformation, automation, and working with APIs.
Databricks/Apache Spark:  Experience working with  Databricks  or  Apache Spark  for distributed data processing and data pipeline orchestration.
SQL Expertise:  Advanced knowledge of SQL, specifically with  Big Query  for creating complex queries and optimizing large-scale datasets.
Data Modeling:  Experience with  data modeling  and designing data architectures that support high-performance analytics and reporting.
ETL Tools:  Experience with  ETL  tools and frameworks (e.g.,  Apache Airflow ,  Dataflow , or  dbt ).
Version Control:  Experience with Git or similar version control systems.
Cloud Data Architecture:  Familiarity with best practices for cloud data architecture, including data lakes, data warehouses, and cloud-native technologies.
Agile Methodology:  Experience working in  Agile  development environments, collaborating in cross-functional teams.
Desired Skills: Data Engineering Frameworks:  Familiarity with frameworks such as  Apache Kafka ,  Apache Beam , or  Flink for real-time data processing.
Machine Learning Integration:  Basic understanding of integrating data pipelines with machine learning models and platforms.
Security & Compliance:  Knowledge of GCP security best practices (e.g., IAM, data encryption, auditing) and compliance standards (e.g., GDPR, HIPAA).
CI/CD Pipelines:  Familiarity with setting up  CI/CD pipelines  for automated testing and deployment of data pipelines.
Education & Experience: Bachelor’s or Master’s degree in  Computer Science ,  Information Technology ,  Engineering , or a related field.
5+ years of experience  as a Data Engineer, with a focus on GCP, data pipelines, and analytics.

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