Senior Data Engineer GCP (ID: 2966)
Senior Data Engineer GCP (ID: 2966)
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6-8years
Not Disclosed
Salary Not Disclosed
1 Vacancy
Job Description
- Design build and manage robust data pipelines and architectures within a Google Cloud Platform (GCP) environment.
- Understand and distinguish between streaming and analytical data and design appropriate ingestion and storage solutions for both within a GCP-based data repository.
- Work with diverse and complex data sources often with low or inconsistent data quality and lineage ensuring reliable data ingestion and transformation.
- Lead the end-to-end development of scalable data engineering solutions that support business intelligence analytics and real-time use cases.
- Collaborate with cross-functional teams including data scientists analysts and architects to ensure data usability availability and governance.
- Implement best practices in data engineering while handling both structured and unstructured data in a secure and cost-efficient manner.
- 6 8 years of total experience with at least 5 years in data engineering roles.
- Hands-on experience with Google Cloud Platform (GCP) including tools like BigQuery Dataflow Pub/Sub Cloud Storage and Data Catalog.
- Proven experience working with diverse data sources including internal enterprise systems third-party APIs and unstructured datasets.
- Strong expertise in setting up and maintaining data pipelines in environments with poor data quality lack of metadata or lineage gaps.
- Proficiency in Python or SQL with a solid understanding of data modeling ETL/ELT processes and performance optimization techniques.
- Familiarity with version control systems CI/CD pipelines and workflow orchestration tools (e.g. Airflow Cloud Composer).
- Translate data architecture principles into practical scalable engineering solutions.
- Navigate ambiguity and derive clarity from messy or incomplete data environments.
- Communicate technical solutions clearly to both technical and non-technical stakeholders.
- Work independently take ownership of projects and proactively address challenges and bottlenecks.
- Balance real-time and batch processing requirements in a GCP data landscape.
- A collaborative and innovative environment that values your technical leadership and practical data engineering skills.
- Opportunities to work with modern cloud-native technologies and solve impactful real-world data challenges.
- A platform to contribute to enterprise-grade data solutions that power analytics and decision-making across teams.
- Professional growth and development in an environment that prioritizes data quality scalability and reliability.
Let s Connect
Want to discuss this opportunity in more detail Feel free to reach out.
Recruiter: Hari Sankar R
Phone:; Extn : 132
Email:
LinkedIn: As a Senior Data Engineer GCP, you will: Design, build, and manage robust data pipelines and architectures within a Google Cloud Platform (GCP) environment. Understand and distinguish between streaming and analytical data, and design appropriate ingestion and storage solutions for both within a GCP-based data repository. Work with diverse and complex data sources, often with low or inconsistent data quality and lineage, ensuring reliable data ingestion and transformation. Lead the end-to-end development of scalable data engineering solutions that support business intelligence, analytics, and real-time use cases. Collaborate with cross-functional teams, including data scientists, analysts, and architects, to ensure data usability, availability, and governance. Implement best practices in data engineering, while handling both structured and unstructured data in a secure and cost-efficient manner. What You Bring to the Table: 6 8 years of total experience, with at least 5 years in data engineering roles. Hands-on experience with Google Cloud Platform (GCP), including tools like BigQuery, Dataflow, Pub/Sub, Cloud Storage, and Data Catalog. Proven experience working with diverse data sources, including internal enterprise systems, third-party APIs, and unstructured datasets. Strong expertise in setting up and maintaining data pipelines in environments with poor data quality, lack of metadata, or lineage gaps. Proficiency in Python or SQL, with a solid understanding of data modeling, ETL/ELT processes, and performance optimization techniques. Familiarity with version control systems, CI/CD pipelines, and workflow orchestration tools (e.g., Airflow, Cloud Composer). You should possess the ability to: Translate data architecture principles into practical, scalable engineering solutions. Navigate ambiguity and derive clarity from messy or incomplete data environments. Communicate technical solutions clearly to both technical and non-technical stakeholders. Work independently, take ownership of projects, and proactively address challenges and bottlenecks. Balance real-time and batch processing requirements in a GCP data landscape. What We Bring to the Table: A collaborative and innovative environment that values your technical leadership and practical data engineering skills. Opportunities to work with modern cloud-native technologies and solve impactful real-world data challenges. A platform to contribute to enterprise-grade data solutions that power analytics and decision-making across teams. Professional growth and development in an environment that prioritizes data quality, scalability, and reliability. Let s Connect Want to discuss this opportunity in more detail? Feel free to reach out. Recruiter: Hari Sankar R Phone: ; Extn : 132 Email: LinkedIn:
Employment Type
Full Time
