Every functional area, in every industry, is on an AI Journey. The power of machine learning to dramatically improve company key performance indicators is being proven every day. But, although we feel every large organization is on an AI journey, the path to value is unclear. There are three key barriers to deploying AI and machine learning at scale:
- Building data pipelines that feed both the development and deployment of machine learning models
- Building API endpoints for both UI applications and other services
- Improving consistency, reducing effort and expanding the ability of data scientists to address the growing range of business problems from prediction to prescription
- Building out the necessary infrastructure to support 100s of machine learning models in production, including the necessary governance and compliance patterns
At Cognizant we are proud to be helping our clients on their journey to AI at scale. We have built practices that bring together the best talent to address these key barriers, and have built unique capability to complement our people:
Our Adaptive Data Foundation brings together our accelerators, partnerships and consulting approach to help clients solve the increasing demands for data
Our Evolutionary AI technology and patents is reducing the effort required to develop deep learning and other sophisticated models. It's particularly adept at addressing prescription problems, from marketing to next best action to supply chain
Our architecture frameworks help clients navigate technology choices throughout the AI process. As well as building capability in close collaboration with the leading cloud providers, we are working with startups that address the critical engineering challenges that machine learning brings
Client demand has meant that we are growing these practices at an unprecedented rate. We are looking for people that can bring existing strengths in data engineering and data science but we want to hire people that share our vision and want to grow their own skills across the problem space. Job description
Are you passionate about transforming and shaping leading organizations? Do you enjoy providing solutions to complex business problems for opportunities requiring in depth knowledge of organizational objectives? Would you like to be part of the leadership team and a major contributor on large deals, which will have a real impact on the company's success?
Come and join our team of Data experts in Munich as a Big Data Engineer and be part of our exciting growth
We offer you an environment where everyone's opinion matters, ideas are openly shared, where change is the norm and where you will work with some of the fastest moving, well-recognized brands in the world. Who are we?
The Artificial Intelligence & Analytics (AI&A) Team is a Technology & Architecture Practice within Cognizant responsible for delivery state of the art solutions on Data modernization, Advanced Analytics and Artificial intelligence across all client industry verticals. What will you do?
Your key responsibilities will be:
- You will be playing a critical role in achieving Cognizant's business objectives. You will be part of the team working closely with our client stakeholders in sourcing the data, transforming it into a service API for different UI applications or other services to cover business use cases
- You will be responsible for the client engagement success from solutioning through delivery.
- You will also be focused on growing our business by providing innovative solutions and adding a real value to our clients. In particular, we are seeking the Big Data Engineers experienced in Cloud Transformation engagements.
What experience are we looking for?
- Work closely with the design teams and Product owners to deliver the solutions for data analysis, data transformation, data aggregation for a service API
- Design and implement the detailed solution to ensure successful operation of ETL pipeline production
- Design and Develop data enrichment and data labeling steps using ML components.
- Co-ordinate with the onsite, nearshore and offshore teams for delivery of technical solution
- Build relationships and credibility with clients to drive "Self-service" approach to own the end-to-end data engineering responsibility
- Work with Application architects and design teams to propose/ develop business case and collaterals for Transformational Initiatives
- Develop the technical solution building on synergies and benefits across the technologies and solution teams
- Research, identify and internally market enabling technologies based on client requirements assisting clients through their journey from ideation to execution creating win-win solution
- Work with Solution teams and Product Owners to understand inefficiencies in clients' existing processes and applications and recommend solutions
- Foster an innovative culture within the team
- Understand the client's requirements, pain points and help the lead architects and designers to arrive at a customized solution by rightly positioning Cognizant assets
- Collaborate with technology groups and other alliances to bring best practices on various technologies and tools
- Strong experience in Cloud Transformation Engagements
- Understand 360 degree of AWS Big Data Architecture
- In-depth knowledge of AWS Tech stack (AWS Fundamentals, Glue, Lambda, Kinesis, Firehose, Cloudwatch, Step functions, EMR, DynamoDB, SNS, SQS, S3, Elastic Search)
- Spark framework, PySpark, hands-on experience in Python
- Strong experience of maintaining code versioning in Github, AWS Code pipeline
- Strong experience in infrastructure as code (preferably Terraform)
- Good to have exposure to Docker, Container technologies
- Define and implement the best practices in AWS Technologies
- Great communication skills, capable to quickly understand the business requirement and provide best-practice solution
- Able to work under pressure to meet aggressive deadlines
- Analyze complex business requirements within User Stories and translate them into the technical solutions and architectural approaches
- Estimate development efforts / story points
- Experience working in DevOps/ Agile working model
- Experience in working within geographically distributed teams (Onsite, Nearshore & Offshore)
- Excellent written and verbal communication skills in German and English
- Customer and Stakeholder Management
- A track record of developing creative solutions
- Highly developed critical thinking, interpretative and analytical skills
- Positive, determined, resilient, confident and resourceful in the face of challenges