GCP Lead Data Engineer

Bengaluru
Full-Time
Hybrid
Senior: 7 to 18 years
Posted on Jul 15 2024

About the Job

Skills

Google Cloud Platform (GCP)
Data Engineering
Big Data Technologies
Data Warehousing
ETL Processes
SQL
Python
Data Modeling

Dear Candidate,

Functional Title: Lead GCP Engineer

Location: MG Road

Start Date: Immediate to 30 Days

Work mode: 2 days/week in office

 

Job Description:

About the Role: We are seeking a Lead GCP Data Engineer who can demonstrate a broad range of technical skills across Google Cloud Platform (GCP) and third-party technologies. As a pivotal member of our team, you will be responsible for designing robust data architectures, developing efficient data pipelines, and optimizing data processing workflows on GCP. Your expertise will be instrumental in driving our data engineering initiatives forward, ensuring scalability, reliability, and performance.

Key Responsibilities:

  • Data Architecture Design: Design scalable and efficient data architectures on GCP that meet the organization's data processing and analysis requirements. Collaborate closely with data scientists, business analysts, and stakeholders to define effective data models and structures.
  • Data Pipeline Development: Develop and implement data pipelines using GCP services such as Google Cloud Storage, BigQuery, Dataflow, and Pub/Sub. Ensure data quality, reliability, and governance throughout the data lifecycle.
  • Data Transformation and Integration: Utilize technologies like Apache Beam, Apache Spark, and Cloud Dataproc to transform and integrate data from diverse sources. Perform data cleansing, aggregation, enrichment, and normalization to support downstream applications and analytics.
  • Performance Optimization: Optimize data processing workflows to enhance performance and efficiency. Monitor pipelines, identify bottlenecks, and implement optimizations such as improved data partitioning, sharding, and leveraging GCP's autoscaling capabilities.
  • Continuous Improvement: Stay abreast of advancements in data engineering and cloud technologies. Explore and implement new GCP features and services to enhance data processing capabilities and drive innovation within the team.
  • Research and Innovation: Conduct research on emerging data engineering technologies, tools, and best practices. Evaluate new methodologies to improve data engineering processes and bring innovative solutions to the organization.
  • Task Automation: Automate data engineering tasks using scripting, workflows, or tools like Cloud Composer and Cloud Functions. Streamline data ingestion, transformation, monitoring, and other operational processes to improve efficiency and reduce manual effort.

Attributes & Competencies:

  • Education: BE/BTech, MTech, or MCA.
  • Experience: Minimum 7+ years in development/migration projects, with at least 3 years focused on GCP. Experience in GCP-based Big Data deployments (batch/real-time) using BigQuery, BigTable, Google Cloud Storage, Pub/Sub, Data Fusion, Dataflow, Dataproc, and Airflow.

Technical Skills:

  • Google Certified Professional Cloud Architect with experience automating and orchestrating workloads on GCP or other public clouds.
  • Proficiency in at least one configuration management system (Chef, Puppet, Ansible, Salt, etc.).
  • Strong programming skills in Python, Go, with expertise in Git and Git workflows.
  • Demonstrated proficiency in CI/CD tools such as Jenkins, TeamCity, or Spinnaker.


Interested candidates can share updated resume at rbisare@kognivera.com

 

About the company

KogniVera is an India-based technology consulting and services company that specializes in conceptualization, design, engineering, and management of digital products. The company brings rich experience and expertise to address the growth needs of enterprises in dynamic industries such as Retail, Financial Services, Insurance, and Healthcare. KogniVera has an unwavering obsession with customer succ ...Show More

Industry

IT Services and IT Consul...

Company Size

51-200 Employees

Headquarter

Bangalore

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