About Cognizant’s AIA Practice
Digital technologies, including analytics and AIA, give companies a once-in-a-generation opportunity to perform orders of magnitude better than ever before. However, clients need new business models built from analyzing customers and business operations at every angle to really understand them.
With the power to apply artificial intelligence and data science to business decisions via enterprise data management solutions, we help leading companies prototype, refine, validate, and scale the most desirable products and delivery models to enterprise scale within weeks
*You must be legally authorized to work in United States without the need of employer sponsorship, now or at any time in the future *
We are Cognizant
Cognizant is looking for an authority and highly motivated GCP Data Engineer to join our Analytics team. You must have a validated background in data-driven problem solving and be able to develop and implement innovative solutions with little to no mentorship. If you are an analytics-minded professional with a passion for unlocking the potential of data, then this role is for you.
Location: Onsite Role in Irving, TX.
Roles & Responsibilities :
Work with implementation teams from concept to operations, providing deep technical subject matter expertise for optimally deploying large scale data solutions in the enterprise, using modern data/analytics technologies on premise and cloud.
Work with data team to efficiently use Google Cloud platform to analyze data, build data models, and generate reports/visualizations.
Integrate massive datasets from multiple data sources for data modelling.
Formulate business problems as technical data problems while ensuring key business drivers are captured in collaboration with product management.
Design pipelines and architectures for data processing. Build and maintain machine learning and statistical models. Extract, Load, Transform, clean, and validate data.
Active Google Cloud Data Engineer Certification Hands on in designing, building and operationalizing large-scale enterprise data solutions and applications using one or more of GCP data and analytics services in combination with 3rd parties - Python, Pyspark, Spark, Hive, Cloud DataProc, Cloud Dataflow, Apache Beam/ composer, Big Table, Cloud BigQuery, Cloud PubSub, Cloud storage Cloud Functions & Github.
Minimum of 5 year of crafting and building production data pipelines from data ingestion to consumption within a hybrid big data architecture, using Cloud Native GCP, Python, SQL etc.
Minimum 5 year of hands-on GCP experience with a minimum of an end to end solution crafted and implemented at production scale.
Salary and Other Compensation:
Applications will be accepted until 09/29/2024.
The annual salary for this position is between $[100,000 – 115,000 USD] depending on the experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
Benefits:
Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
- Medical/Dental/Vision/Life Insurance
- Paid holidays plus Paid Time Off
- Long-term/Short-term Disability
- Paid Parental Leave
- Employee Stock Purchase Plan
Disclaimer:
The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
The Cognizant community:
We are a high caliber team who appreciate and support one another. Our people uphold an energetic, collaborative and inclusive workplace where everyone can thrive.
- Cognizant is a global community with more than 345,000 associates around the world.
- We don’t just dream of a better way – we make it happen.
- We take care of our people, clients, company, communities and climate by doing what’s right.
- We foster an innovative environment where you can build the career path that’s right for you.
