GCP Data Architect

3 weeks ago

Pune, India EXL Full time

As a GCP Data Engineer Architect, you will be responsible for architecting enterprise data solutions for migration, transformation or modernization on Google Cloud Platform (GCP) integrating native GCP services and other 3rd party data solutions. You will collaborate with cloud partners and our cross-functional teams to enable sector-specific use cases. Your responsibilities will involve technology adoptions pertaining to AI/ML, Generative AI, Advanced analytics, serverless and service driven ecosystem for data led and AI enabled digital transformations.

Expert proficiency in comprehending the principles for large scale architecting, solutioning and operationalization of data pipelines, warehouses, data lakes, analytics platforms and activation services on GCP is crucial. We are looking for professionals with solid experience on design, delivery, and implementation of GCP infrastructure and solutions along with 3rd party technologies on Google Cloud.

Position – GCP Data Engineer - Architect

Work Location – Pune (Hybrid)

Experience - 12+ Years

Must have skills:

  • 12+ years of proven experience as an Architect in Big Data Engineering .
  • Mandatory Technical Proficiency - Hands-on experience with Python , PySpark , Google Cloud Full Stack Architecture , SQL , DevOps, Databricks, DBT & Terraform .
  • Experience with Google Cloud Services such as Streaming +Batch, Cloud Storage, Cloud Dataflow , Data Proc , Big Query & Big Table
  • Proven real time exposure and use of contemporary data mining, cloud computing and data management ecosystem like Google Cloud, Hadoop , HDFS and Spark .
  • Proficient in Data Modelling that can represent complex data structures while ensuring accuracy, consistency, and efficiency; data warehousing, and ETL processes.
  • Ability to perform system analysis and assessment of existing Systems Design and operating methodologies leveraging in-depth knowledge of big data technologies and ecosystems.
  • Experience with GitHub , Anaplan , Looker & Power BI ,
  • Excellent problem-solving skills and the ability to address complex technical challenges.
  • Strong communication and leadership skills.

Good to have:

  • Experience with Apigee , Apollo GraphQL .
  • Experience with Quality Assurance , Agile , Documentation & Presentation .
  • Experience with serverless Data warehousing concepts,
  • Additional programming/scripting languages: JavaScript , Java .
  • Knowledge of Snowflake , ML - Machine Learning , Gen AI (LLMs ), Marketing activation.

Role & Responsibilities:

  • Solution Design: Participate in in requirements gathering and architectural discussions. Define technical requirements and create solution designs that align with business goals and objectives.
  • Responsible for Overall quality of Engineering builds and Architecture.
  • Overall Solutions architecture of Data foundations & use-cases on BTDP
  • Technical Leadership: Lead creation of technical design/specifications and provide technical leadership and guidance to development teams, promoting best practices. Provide expertise with Master Data Management , Reference Data Management, Data Quality , Meta Data Management and Data Governance in General.
  • Programming Hands on: Develop and maintain software components using Python , PySpark , and GCP services to process and analyze large datasets efficiently. Build data pipelines and perform data transformations.
  • Enforce consistent standards and quality through end-to-end review of all artefacts (incl. BRD, HLD, LLD, Data Models, STTMs, UI-UX, NFRs, Code, Test, PBI architecture design.
  • POC and Pilot of new reusable frameworks, tools & technologies.
  • Evaluate newest technologies for optimization opportunities and future enhancement needs like self-serve and ad hoc reporting. Implement necessary infrastructure for optimal and efficient ETL from a disparate data.
  • Performance Optimization: Identify and address performance bottlenecks, ensuring the system meets required throughput and latency targets.
  • Security and Compliance: Ensure that data solutions adhere to security and compliance standards, implementing necessary controls and encryption mechanisms.
  • Scalability: Architect scalable and highly available data solutions, considering both batch and real-time processing.
  • Documentation: Create and maintain comprehensive technical documentation to support the development and maintenance of data solutions.

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