GCP Data Engineer
At a glance
Mid-level Data Engineering role at Fa Ewjt Saasfaprod1. Gurugram · full-time.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Build automated ETL or ELT pipelines with Python or Scala solutions, or Cloud Data Fusion
- Create efficient data models for analytical and transactional workloads
- Use GCP tools such as BigQuery, Dataproc, Airflow and Dataflow to support data processing
- Set up delivery pipelines and monitor production workflows using CI/CD, logging and monitoring tools
What you bring
- At least six years working in data engineering or a related area
- A degree in computer science or a related discipline
- Strong Python and SQL skills, plus familiarity with GCP service APIs and SDKs
Who this fits
This mid-level role suits someone comfortable building data pipelines and models on GCP, working with analysts and business stakeholders, and explaining technical ideas to non-technical audiences. The position is hybrid in Gurugram, India.
From the employer
Technical Skills:-
1. Core Data Engineering Skills
Big Data Technologies: Proficiency in using GCP's big data tools like:
BigQuery: For data warehousing and SQL analytics.
Dataproc: For running Spark and Hadoop clusters.
Airflow: For pipeline Orchestration
Dataflow: For stream and batch data processing.(High level Idea)
Pub/Sub: For real-time messaging and event ingestion.(High level Idea)
Data Modeling: Experience/Knowledge on designing scalable, efficient data models for OLAP and OLTP use cases.
ETL/ELT Pipelines:
Expertise in building automated, scalable, and reliable pipelines using custom Python/Scala solutions or Cloud Data Fusion.
2. Programming and Scripting
Strong coding skills in Python, SQL, and optionally Java/Scala.
Familiarity with APIs and SDKs for GCP services to build custom data solutions.
3. Cloud Infrastructure
Understanding of GCP services such as Cloud Storage, Compute Engine, and Cloud Functions.
Familiarity with Kubernetes (GKE) and containerisation for deploying data pipelines. (Optional but Good to have)
4. DevOps and CI/CD
Experience setting up CI/CD pipelines using Cloud Build, GitHub Actions, or other tools.
Monitoring and logging tools like Cloud Monitoring and Cloud Logging for production workflows.
Soft Skills: -
1. Innovation and Problem-Solving
Ability to think creatively and design innovative solutions for complex data challenges.
Experience in prototyping and experimenting with cutting-edge GCP tools or third-party integrations.
Strong analytical mindset to transform raw data into actionable insights.
2. Collaboration
Teamwork: Ability to collaborate effectively with data analysts, and business stakeholders.
Communication: Strong verbal and written communication skills to explain technical concepts to non-technical audiences.
3. Adaptability and Continuous Learning
Open to exploring new GCP features and rapidly adapting to changes in cloud technology
1. Core Data Engineering Skills
Big Data Technologies: Proficiency in using GCP's big data tools like:
BigQuery: For data warehousing and SQL analytics.
Dataproc: For running Spark and Hadoop clusters.
Airflow: For pipeline Orchestration
Dataflow: For stream and batch data processing.(High level Idea)
Pub/Sub: For real-time messaging and event ingestion.(High level Idea)
Data Modeling: Experience/Knowledge on designing scalable, efficient data models for OLAP and OLTP use cases.
ETL/ELT Pipelines:
Expertise in building automated, scalable, and reliable pipelines using custom Python/Scala solutions or Cloud Data Fusion.
2. Programming and Scripting
Strong coding skills in Python, SQL, and optionally Java/Scala.
Familiarity with APIs and SDKs for GCP services to build custom data solutions.
3. Cloud Infrastructure
Understanding of GCP services such as Cloud Storage, Compute Engine, and Cloud Functions.
Familiarity with Kubernetes (GKE) and containerisation for deploying data pipelines. (Optional but Good to have)
4. DevOps and CI/CD
Experience setting up CI/CD pipelines using Cloud Build, GitHub Actions, or other tools.
Monitoring and logging tools like Cloud Monitoring and Cloud Logging for production workflows.
Graduate in Computer Science, or related field. 6+ years of experience in data engineering or related field.
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