Senior Data & AI Solution Architect

DXC Technology•Newark, NJ

1d•$158,300 - $293,900•Remote

About The Position

DXC Technology helps global companies run their mission-critical systems and operations while modernizing IT, optimizing data architectures, and ensuring security and scalability across public, private, and hybrid clouds. The world’s largest companies and public sector organizations trust DXC to deploy services across the Enterprise Technology Stack to drive new levels of performance, competitiveness, and customer experience.

Requirements

Expertise in designing conceptual, logical, and physical architecture diagrams and flows for data engineering, including data ingestion patterns, transformation, warehousing, pipelines, and big data technologies (e.g., Hadoop, Spark, AWS Redshift, Azure Data Lake, GCP BigQuery, Snowflake, Databricks, Synapse), ETL tools (IDMC, Talend, SSIS, FIVETRAN, DBT, Ab Initio, Pentaho, Striim, AWS Glue, Azure Data Factory, Matillion, etc.)
Developing data security strategies aligned with industry regulations (GDPR, HIPAA, PCI DSS, PII, ISO), including encryption, data masking, and access controls for sensitive data.
Design scalable, secure cloud data architectures that balance performance, cost optimization, and data security. Architect cloud-native solutions and lead app modernization initiatives to migrate legacy applications to AWS, Azure, GCP, Oracle, improving scalability, performance, and cost efficiency.
Incorporating DevOps principles like CI/CD pipelines, infrastructure as code, and automated testing into data solutions to streamline deployment and management.
Ability to explore and design data integration architecture from data warehouses/data lakes and other data sources to consumption applications.
Understanding of data structures, dimensional modeling, and data warehousing concepts including data vault concepts, star schema, SCDs.
Familiarity with programming languages (e.g., SQL, Python, Java, Scala) and data manipulation techniques.
Bachelor’s degree or equivalent combination of education and experience.
Bachelor’s degree in computer science, information technology, or related field.
Overall Experience in Data and Analytics of more than 12 years.
Experience in client interaction as a pre-sales solutions architect of more than 5 years
Experience with a broader landscape of Data & AI products and services.
Effective communication, written, presentation, interpersonal, and listening skills.
Ability to create and maintain formal and informal networks.
Ability to publicly represent the company with internal and external clients.
Ability to use own judgment and initiative in problem resolution.
Ability to present ideas, goals, problems, outcomes, and processes to a diverse audience.
Must be legally authorized to work in the United States without requiring sponsorship now or in the future.

Nice To Haves

Assess the client data landscape, identify data quality issues, and design data governance frameworks, including data ownership, access controls, and data quality standards. Familiarity/Expertise with MDM and data governance and security concepts and tools – Collibra, Purview, IDMC, Alation, Erwin Data Intelligence, Databricks Unity Catalog, Atlan
Create architecture patterns and solution design for BI implementation, ad hoc data analysis, semantic layer, BI data modeling, BI optimization, BI governance, BI distribution, and consumption. Familiarity with optimizing data refreshes, dashboards, and reports aligned with customer requirements. Expertise in BI tools and platforms like Power BI, Tableau, Qlik, Cognos, MicroStrategy, etc.
Develop customized AI/ML solution architectures across major AI platforms, including MLOps, AIOps, and AI delivery, including data pipeline setup, deployment, training, testing, model selection, and infrastructure considerations based on customer needs. Familiarity with AI/ML-related technologies and tools such as MLflow, Kubeflow, Kubernetes, TensorFlow, PyTorch, AWS SageMaker, Azure ML Studio, DataRobot, Databricks MLflow, and Snowflake ML.
Evaluate and select suitable generative AI models (like GPT-3, BERT, PaLM) based on project requirements. Design the overall system architecture to integrate LLMs into existing applications or build new AI-powered products. Plan data pipelines, processing workflows, and model deployment strategies. Provide technical guidance to development teams on implementing generative AI solutions. Guide the selection of appropriate tools, frameworks, and cloud platforms for building and deploying Gen AI systems. Stay current with the latest advancements in generative AI research and technologies to keep solutions innovative. Develop prototypes and proofs of concept to validate Gen AI solutions. Optimize model performance, including fine-tuning LLMs to specific tasks and domains. Implement robust monitoring and evaluation mechanisms to track the effectiveness of deployed Gen AI systems.

Responsibilities

Develops and drives large and/or complex business solutions for targeted/assigned customers, providing in-depth solutions architecture recommendations based on specific customer needs.
Actively research customers to determine business issues, establish technical credibility, and cultivate relationships with senior IT executives.
Provide solution architecture and strategic guidance during the solution development process to ensure alignment with overall company sales and client business strategy.
Deliver and sell the technical solution strategy and vision to senior client executives, ensuring the solution meets client expectations and requirements.
Research industry, market, and IT services best practices and trends to ensure company solutions meet client needs. Leverage partner solutions to continuously solve customer needs.
Contribute to the Data & AI offering development by collaborating with the global teams and educating sellers, client partners, and clients.
Function as a technical resource and mentor for less experienced Sales Solutions personnel.
Analyze a client's technology stack, considering data ingestion, storage, processing, analytics, security, governance, access, and visualization needs.
Create customized architectures, including data ingestion, storage, processing, data warehousing, data pipelines, reporting & dashboards, and data governance strategies.
Deliver presentations showcasing proposed solutions, highlighting features and functionality.
Build small-scale prototypes to demonstrate the feasibility and potential impact of BI and data engineering solutions.
Craft comprehensive technical responses to requests for information and proposals, outlining proposed solutions and pricing.
Work closely with sales representatives to qualify leads, address technical concerns, and articulate the business value of the solutions.
Engage with prospective clients to assess their data needs, identify pain points, and translate business requirements into technical solutions.
Collaborate with sales representatives to answer technical questions, address concerns, and qualify potential leads.