We are looking for a skilled and motivated Data Engineer with strong experience in Python programming and Google Cloud Platform (GCP) to join our data engineering team. The ideal candidate will be responsible for designing, developing, and maintaining robust and scalable ETL (Extract, Transform, Load) data pipelines. The role involves working with various GCP services, implementing data ingestion and transformation logic, and ensuring data quality and consistency across systems.

Key Responsibilities:

Design, develop, test, and maintain scalable ETL data pipelines using Python.
Work extensively on Google Cloud Platform (GCP) services such as:
Dataflow for real-time and batch data processing
Cloud Functions for lightweight serverless compute
BigQuery for data warehousing and analytics
Cloud Composer for orchestration of data workflows (based on Apache Airflow)
Google Cloud Storage (GCS) for managing data at scale
IAM for access control and security
Cloud Run for containerized applications
Perform data ingestion from various sources and apply transformation and cleansing logic to ensure high-quality data delivery.
Implement and enforce data quality checks, validation rules, and monitoring.
Collaborate with data scientists, analysts, and other engineering teams to understand data needs and deliver efficient data solutions.
Manage version control using GitHub and participate in CI/CD pipeline deployments for data projects.
Write complex SQL queries for data extraction and validation from relational databases such as SQL Server, Oracle, or PostgreSQL.
Document pipeline designs, data flow diagrams, and operational support procedures.

Required Skills:

4–8 years of hands-on experience in Python for backend or data engineering projects.
Strong understanding and working experience with GCP cloud services (especially Dataflow, BigQuery, Cloud Functions, Cloud Composer, etc.).
Solid understanding of data pipeline architecture, data integration, and transformation techniques.
Experience in working with version control systems like GitHub and knowledge of CI/CD practices.
Strong experience in SQL with at least one enterprise database (SQL Server, Oracle, PostgreSQL, etc.).

Key Responsibilities:

Design, develop, test, and maintain scalable ETL data pipelines using Python.
Work extensively on Google Cloud Platform (GCP) services such as:
Dataflow for real-time and batch data processing
Cloud Functions for lightweight serverless compute
BigQuery for data warehousing and analytics
Cloud Composer for orchestration of data workflows (based on Apache Airflow)
Google Cloud Storage (GCS) for managing data at scale
IAM for access control and security
Cloud Run for containerized applications
Perform data ingestion from various sources and apply transformation and cleansing logic to ensure high-quality data delivery.
Implement and enforce data quality checks, validation rules, and monitoring.
Collaborate with data scientists, analysts, and other engineering teams to understand data needs and deliver efficient data solutions.
Manage version control using GitHub and participate in CI/CD pipeline deployments for data projects.
Write complex SQL queries for data extraction and validation from relational databases such as SQL Server, Oracle, or PostgreSQL.
Document pipeline designs, data flow diagrams, and operational support procedures.

Required Skills:

4–8 years of hands-on experience in Python for backend or data engineering projects.
Strong understanding and working experience with GCP cloud services (especially Dataflow, BigQuery, Cloud Functions, Cloud Composer, etc.).
Solid understanding of data pipeline architecture, data integration, and transformation techniques.
Experience in working with version control systems like GitHub and knowledge of CI/CD practices.
Strong experience in SQL with at least one enterprise database (SQL Server, Oracle, PostgreSQL, etc.).

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About Egen Solutions

Founded :

2009

Type :

Services

Size :

100-1000

Stage :

Profitable

About

We build next-generation cloud-native data platforms and applications. Our clients rely on us to architect and execute next generation technology strategies. From building and migrating to cloud-native data platforms to designing new modern business models.

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