GCP Data Engineer

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Google Cloud Platform (GCP) Data Engineer will be responsible for architecting transformation and modernization of enterprise data solutions on GCP integrating native GCP services and 3rd party data technologies.

A solid experience and understanding of considerations for large scale architecting, solutioning and operationalization of data warehouses, data lakes and analytics platforms on GCP is a must.

We are looking for candidates who have a broad set of technology skills across these areas and who can demonstrate an ability to design right solutions with appropriate combination of GCP and 3rd party technologies for deploying on GCP cloud.

Key responsibilities may include :

• Lead a team of data engineers in designing, developing, testing, and deploying high performance data analytics solutions in GCP.
• As a Data Engineer, work with implementation teams from concept to operations, providing deep technical subject matter expertise for successfully deploying large scale data solutions in the enterprise, using modern data / analytics technologies on premise and cloud
• Experience in building solution architecture, provision infrastructure, secure and reliable data-centric services and application in GCP
• Implement end-to-end data analytics solutions (from data ingestion through visualization) for large-scale, complex client environments
• Analyze and understand Big Data and analytical technologies on GCP and provide thought leadership to clients to assist with defining their architecture, data, analytics strategies
• Communicate complex technical topics to non-technical business and sr. executives
• Experience working with recommendation engines, data pipelines, or distributed machine learning and experience with data analytics and data visualization techniques and software
• Supporting Data migration and transformation projects.
• Knowledge on Google AutoML framework to build intelligence into the data pipelines.

Travel may be required for this role. The amount of travel will vary from 25% to 100% depending on business need and client requirements.

• GCP Services : Minimum of 5 year's experience in any cloud platform including 2 years of Deep experience with GCP data and analytics services including Spark, Cloud DataProc, Cloud Dataflow, Apache Beam, BigTable, Cloud BigQuery, Cloud PubSub, Cloud Functions
• Data Warehousing & Pipelines : Minimum of 3 years of proven ability to re-architect and re-platform on-premise data warehouses to GCP, and design / build production data pipelines within hybrid architectures using Java, Python, or Scala.
• Data Platform Architecture : Minimum of 3 years of expertise in architecting and implementing next-generation data and analytics platforms on GCP, including data engineering, ingestion, and curation functions using GCP native or custom programming.
• Data Lake & Ingestion : Minimum of 3 years of hands-on experience architecting & designing data lakes on GCP, and implementing data ingestion solutions using GCP native services or 3rd-party tools like Talend / Informatica
• Data Modeling & Optimization : Minimum of 3 years of proficiency in designing and optimizing data models on GCP using BigQuery and BigTable
• Vertex AI : Minimum of 2 years of proficiency in using Google Cloud's Vertex AI platform for building, deploying, and managing machine learning models, including GenAI models.
• MLOps for GenAI : Minimum of 2 years of experience in implementing MLOps practices for the development, deployment, and monitoring of GenAI models.
• Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate's Degree, must have a minimum 6 years work experience)

Preferred Qualifications

• Metadata Management, Governance & Security : Experience architecting and implementing metadata management, data governance, and security for data platforms on GCP.
• Performance Engineering : Ability to design operations architecture and conduct performance engineering for large-scale data lakes in production
• Hadoop / NoSQL : Experience architecting and operating large production yearsHadoop / NoSQL clusters on-premise or in the cloud
• Self-Service Data Prep : Familiarity with introducing and operationalizing self-service data preparation tools (e.g., Trifacta, Paxata) on GCP
• SQL : 3 + years experience writing complex SQL queries and stored procedures
• Generative AI Studio : Experience with Generative AI Studio for prototyping and experimenting with generative AI models.
• Model Garden : Familiarity with Google's Model Garden and its offerings for accessing and deploying pre-trained GenAI models.
• Certifications : Google Certified Professional Data Engineer

Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience.

As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired in California, Colorado, District of Columbia, Maryland, New York or Washington as set forth below.

We accept applications on an on-going basis and there is no fixed deadline to apply.

Information on benefits is here.

Role Location Annual Salary Range

California $93,400 to $224,600

Colorado $93,400 to $194,100

District of Columbia $99,500 to $206,700

New York $86,500 to $224,600

Maryland $86,500 to $179,700

Washington $99,500 to $206,700

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