Posted:
9/17/2024, 5:15:41 AM
Location(s):
Washington, United States ⋅ Pennsylvania, United States ⋅ Ohio, United States ⋅ Pittsburgh, Pennsylvania, United States ⋅ Seattle, Washington, United States ⋅ Phoenix, Arizona, United States ⋅ Columbus, Ohio, United States ⋅ Wisconsin, United States ⋅ Texas, United States ⋅ Irving, Texas, United States ⋅ Arizona, United States ⋅ Milwaukee, Wisconsin, United States
Experience Level(s):
Mid Level ⋅ Senior
Field(s):
Data & Analytics
Workplace Type:
Hybrid
Are you ready to step up to the New and take your technology expertise to the next level?
Join Accenture and help transform leading organizations and communities around the world. The sheer scale of our capabilities and client engagements and the way we collaborate, operate and deliver value provides an unparalleled opportunity to grow and advance. Choose Accenture and make delivering innovative work part of your extraordinary career.
As part of our Google Cloud Platform practice, you will lead technology innovation for our clients through robust delivery of world-class solutions. There will never be a typical day and that’s why people love it here. The opportunities to make a difference within exciting client initiatives are unlimited in the ever-changing technology landscape. You will be part of a growing network of technology experts who are highly collaborative taking on today’s biggest, most complex business challenges. We will nurture your talent in an inclusive culture that values diversity. Come grow your career in technology at Accenture!
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
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with 750,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. We are uniquely able to deliver tangible outcomes because of our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song. These capabilities, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities. Visit us at www.accenture.com
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Website: https://accenture.com/
Headquarter Location: Dublin, Dublin, Ireland
Employee Count: 10001+
Year Founded: 1989
IPO Status: Public
Last Funding Type: Grant
Industries: Business Information Systems ⋅ Construction ⋅ Consulting ⋅ Information Services ⋅ Information Technology ⋅ Infrastructure ⋅ Management Consulting ⋅ Outsourcing