Senior Principal Consultant - GCP Data Engineer

Inviting applications for the role of Senior Principal Consultant - GCP Data Engineer

We are seeking a highly experienced and visionary Senior Google Cloud Data Engineer to spearhead the design, development, and optimization of our data infrastructure and pipelines on the Google Cloud Platform (GCP).

With over relevantyears of hands-on experience in data engineering, you will be instrumental in building scalable, reliable, and performant data solutions that power our advanced analytics, machine learning initiatives, and real-time reporting. You will provide technical leadership, mentor team members, and champion best practices for data engineering within a GCP environment.

Responsibilities

• Should have end-to-end solutioning experience in GCP data and have good implementation knowledge on data modernization , data mesh/febric/microservice and event based solution.

• Architect, design, and implement end-to-end data pipelines on GCP using services like Dataflow, Cloud Composer (Airflow), Pub/Sub, and BigQuery.

• Build and optimize data warehousing solutions leveraging BigQuery%27s capabilities for large-scale data analysis.

• Design and implement data lakes on Google Cloud Storage, ensuring efficient data organization and accessibility.

• Should have experience intoBigquery-Vertex AI and MLops.

• Develop and maintain scalable ETL/ELT processes to ingest, transform, and load data from diverse sources into GCP.

• Develop DBT Pipeline for ETL solution. Should have hand-on experience for moving the data between the medallion architecture,

• Implement robust data quality checks, monitoring, and alerting mechanisms within the GCP data ecosystem.

• Collaborate closely with data scientists, analysts, and business stakeholders to understand their data requirements and deliver high-impact solutions on GCP.

• Lead the evaluation and adoption of new GCP data engineering services and technologies.

• Implement and enforce data governance policies, security best practices, and compliance requirements within the Google Cloud environment.

• Provide technical guidance and mentorship to other data engineers on the team, promoting knowledge sharing and skill development within the GCP context.

• Troubleshoot and resolve complex data-related issues within the GCP infrastructure.

• Contribute to the development of data engineering standards, best practices, and comprehensive documentation specific to GCP.

Qualifications we seek in you!

Minimum Qualifications / Skills

• Bachelor%27s or Master%27s degree in Computer Science, Engineering, or a related field.

• Relevant years of progressive experience in data engineering roles, with a strong focus on cloud technologies.

• Deep and demonstrable expertise with the Google Cloud Platform (GCP) and its core data engineering services (e.g., BigQuery, Dataflow, Cloud Composer, DBT, Dataform, Cloud Storage, Pub/Sub, Cloud Functions).

• Extensive experience designing, building, and managing large-scale data pipelines and ETL/ELT workflows specifically on GCP.

• Strong proficiency in SQL and at least one programming language relevant to data engineering on GCP (e.g., Python).

• Comprehensive understanding of data warehousing concepts, data modeling techniques optimized for BigQuery, and NoSQL database options on GCP (e.g., Cloud Bigtable, Firestore).

• Solid grasp of data governance principles, data security best practices within GCP (IAM, KMS), and compliance frameworks.

• Excellent problem-solving, analytical, and debugging skills within a cloud environment.

• Exceptional communication, collaboration, and presentation skills, with the ability to articulate technical concepts clearly to various audiences.

Preferred Qualifications/ Skills

• Google Cloud certifications relevant to data engineering (e.g., Professional Data Engineer and PCA Certification)

• Experience with infrastructure-as-code tools for GCP (e.g., Terraform, Deployment Manager).

• Familiarity with data streaming technologies on GCP (e.g., Dataflow, Pub/Sub).

• Experience with machine learning workflows and MLOps on GCP (e.g., Vertex AI).

• Knowledge of containerization technologies (Docker, Kubernetes) and their application within GCP data pipelines (e.g., Dataflow FlexRS).

• Experience with data visualization tools that integrate well with GCP (e.g., Looker).

• Familiarity with data cataloging and data lineage tools on GCP (e.g., Data Catalog).

• Experience in [mention specific industry or domain relevant to your company].

• Proven experience in leading technical teams and mentoring junior engineers in a GCP environment.