| Job Opening :: Solution Architect - Onsite at Remote, Remote, USA |
| Email: [email protected] |
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From: Jaswanth, Axiustek [email protected] Reply to: [email protected] Hi Team We Have Multiple Position, If any candidate fits for this position Please share the resume Need Only Architect Candidate willing to go Onsite to those location For Every position We have JD in Below SN Position Location 1 Solution Architect - GEN AI Architect Plano, TX (Onsite) 2 Solution Architect - Data Governance Plano, TX (Onsite) 3 Solution Architect - AI ML Data Modeling Plano, TX (Onsite) 4 Solution Architect - DSA/ BIA Plano, TX (Onsite) 5 Solution Architect - Azure Data Bricks Plano, TX (Onsite) 6 Solution Architect - Data Architect (Google Big Query) Houston, TX (Onsite) Data Architect Azure Databricks 15+ years of Data Solutions Design/Development Experience with at-least 2+ years working as Lead Data Architect for a medium to large sized project or proposal Be able to Design & Develop and Discuss with client architect/team around data architecture and data related issues Analyze and assess the impact of the requirements on the data and its lifecycle, Lead the data architecture design of medium to complex data analytics applications and systems Strong experience in Azure with hands-on experience in any 2 or more of : Azure SQL DB ,Azure SQL Managed Instance ,Azure Data Lake Store, Azure Cosmos DB, IoT/Event Hub Strong experience in defining end to end data engineering solutions with hands-on in any 2 or more of : Azure Data Factory, Azure DataBricks, Azure API for data, Logic Apps, T-SQL Experience with design/develop 1 or more of below is preferred o Azure Synapse Analytics or Snowflake on Azure based solutions o Data Migration to Azure o Azure Analysis Services & PowerBI / Tableau based analytical reporting o Big-data Solutions leveraging HD-Insight based solutions OR Spark-Scala Batch/Micro-Batch OR Kafka based Streaming o Azure ML / AI or Any Analytical /Data Science (Python/R/SAS etc.) leveraged solutions o Data Governance Expertise with any of industry leading tools with training/exposure on Azure Purview Exposure to Azure DevOps Implementation, DevSecOps / DataOps Methods preferred Should be able to drive the technology design meetings, propose technology design and architecture Demonstrate breadth of experience in various client scenarios and situations Gen AI Architect Responsibilities Gathers, interprets, and manipulates structured and unstructured data to enable analytical solutions for the business. Selects the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs. Build various ML Models within the Model guidelines and framework. Consults with peers for guidance, as needed. Translates business requirements into specific analytical questions, build ML Models and present model outcomes to non-technical business colleagues. Consults with Data Engineering, IT, the business, and other internal stakeholders to deploy analytical solutions Stay current with emerging trends and technologies in data quality management, data profiling, data cleansing tools and AI/ML. Collaborate with data governance teams to ensure compliance with regulatory requirements and industry and legal standards related to data quality and privacy. Able to identify GenAI use cases given in various business scenarios and come up with possible solutions. Familiar with various GenAl technologies, Prompt Engineering, RAG etc Skills & Qualifications 10 to 12 years of relevant experience, and 6+ years of experience in data science, machine learning, quantitative analytics (Mathematics, Statistics or Operational Research etc) roles Masters degree in computer science, Statistics, or a related field (Mathematics, Operational Research, Data Science) Experience in Building and validating statistical, machine learning, and other advanced analytics models. Experience in Regression (multiple, Logistic etc), Classification (Decision Tree, Random Forest, XGBoost etc) and Time series Forecasting models (ARIMA), Segmentation, NLP, Deep Learning and Graph Analytics. Experience in Data Mining, Python, R, SQL, and familiarity with ML technologies Experience in using ML Libraries. Working Experience in Domino Data Lab, AWS Sagemaker, Snowflake are a plus Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop) AI ML Data Modeling Responsibilities Gathers, interprets, and manipulates structured and unstructured data to enable analytical solutions for the business. Selects the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs. Build various ML Models within the Model guidelines and framework. Consults with peers for guidance, as needed. Translates business requirements into specific analytical questions, build ML Models and present model outcomes to non-technical business colleagues. Consults with Data Engineering, IT, the business, and other internal stakeholders to deploy analytical solutions Stay current with emerging trends and technologies in data quality management, data profiling, data cleansing tools and AI/ML. Collaborate with data governance teams to ensure compliance with regulatory requirements and industry and legal standards related to data quality and privacy. Able to identify GenAI use cases given in various business scenarios and come up with possible solutions. Familiar with various GenAl technologies, Prompt Engineering, RAG etc Skills & Qualifications 10 to 12 years of relevant experience, and 6+ years of experience in data science, machine learning, quantitative analytics (Mathematics, Statistics or Operational Research etc) roles Masters degree in computer science, Statistics, or a related field (Mathematics, Operational Research, Data Science) Experience in Building and validating statistical, machine learning, and other advanced analytics models. Experience in Regression (multiple, Logistic etc), Classification (Decision Tree, Random Forest, XGBoost etc) and Time series Forecasting models (ARIMA), Segmentation, NLP, Deep Learning and Graph Analytics. Experience in Data Mining, Python, R, SQL, and familiarity with ML technologies Experience in using ML Libraries. Working Experience in Domino Data Lab, AWS Sagemaker, Snowflake are a plus Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop) Excellent problem-solving, analytical skills and attention to detail, with the ability to identify patterns, trends, and anomalies in data. Ability to write code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency). Experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, HQL, NoSQL, etc. Experience in working with structured, semi-structured, and unstructured data files such as delimited numeric data files, JSON/XML files, and/or text documents, images, etc. Strong communication and collaboration skills, with the ability to effectively interact with technical and non-technical stakeholders. Job Title: Data Governance Coordinate on Data Analytics on new requirements, priorities and deliverables. Instrumental to set up and establish best practices across the organization to govern data (processes, roles, policies, tools, etc.) Develop necessary artefacts to support the data governance organization Collaborate with stakeholders from multiple disciplines to translate data requirements into clearly defined and easily understood documents (data glossaries, dictionaries, policies, data flows, etc.) Support and orchestrate the data governance team(s) to set priorities and implement data governance practices Drive discussions with the data governance teams(s) to help set up data policies to govern data Collaborate with the data governance team(s) to scale to the entire business and empower them to become Coordinate on Data Analytics on new requirements, priorities and deliverables. Instrumental to set up and establish best practices across the organization to govern data (processes, roles, policies, tools, etc.) Develop necessary artefacts to support the data governance organization Collaborate with stakeholders from multiple disciplines to translate data requirements into clearly defined and easily understood documents (data glossaries, dictionaries, policies, data flows, etc.) Support and orchestrate the data governance team(s) to set priorities and implement data governance practices Drive discussions with the data governance teams(s) to help set up data policies to govern data Collaborate with the data governance team(s) to scale to the entire business and empower them to become self-sufficient to govern data Identify strengths and weaknesses in the data governance organization to recommend ways to improve Facilitate processes to address transversal, cross-business data governance issues Help set-up smooth processes between business and IT to implement solutions to govern data Lead initiatives with data governance tool(s) (e.g. MDM, meta-data management, data quality reporting) Measure and monitor data quality Define, drive and prioritize data quality remediation plans. Decision Science Analyst (DSA) / Business Intelligence Analyst (BIA) Job responsibilities: should have is quantitative analytics experience with some fundamental statistical knowledge Apply statistical and mathematical techniques and provide decision support for business Gather, manipulate and synthesize data, models to draw conclusions and make recommendations Leverage business/ analytical knowledge to participate in discussions with cross functional teams Document assumptions, methodology, validation and testing Present results and recommendations to wider audiences Use visualization techniques to support your argument Support identifying and gathering the relevant and quality data sources required through testing or exploratory data analysis (EDA). Utilize data & analytics to provide superior actionable business insights and recommendations Preferred Skills & Qualifications: Degree in Economics, Mathematics. Finance, Statistics, or any other quantitative discipline with 8 years of experience in Quantitative analytics field Strong Expertise and Experience in SQL, SAS, and Tableau. Demonstrate competency in mathematical and statistical techniques and approaches used to drive fact-based decision-making. Working knowledge of identifying, documenting and analyzing business and/or data requirements Knowledge of industry best practices Experience in developing reports and Dashboards Expertise in deriving insights from various analysis and present outcomes to different set of stakeholders. Working experience in financial domain in preferred Data Architect (Google Big Query) 15+ years of IT Industry experience 10 plus years of hands on development experience in areas of Data Warehouse and Data Lake using industry standard tools and technology Must have good technical expertise on Google Cloud- Data Eco-system like Big Query, DataProc and DataFlow. Must have ETL / ELT / Data acquisition / data ingestion development and architecture experience Must have good understanding of realtime streaming, API / microservices based data ingestion. Development experience in Kafka and data flow is desired. Ability to ingestion data for full load/ CDC/ and micro-batches for structured & unstructured data. It is essential that candidate has good experience in CICD/ DevOps and Github integration, release management, production deployment and agile development process. 2+ years of experience in SAP S3/ S4 HANA will is desired. Good understanding of HR, Finance, Supply chain or utility domain knowledge is desired by not mandatory. 5 plus years of experience in leading data modeling, data architecture for data lake/ Data Warehouse is necessary Must have good understanding of Advance Analytics, Data Science, AI & Machine Learning. Ability setup analytical sandbox, one click deployment and environment provisioning Keywords: artificial intelligence machine learning sthree database sfour rlang information technology golang Texas Job Opening :: Solution Architect - Onsite [email protected] |
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| 11:14 PM 05-Dec-24 |