Principal Architect (Data and Cloud) - Neoware Technology Solutions Private Limited Principal Architect (Data and Cloud) Requirements More than 10 years of experience in Technical, Solutioning, and Analytical roles. 5+ years of experience in building and managing Data Lakes, Data Warehouse, Data Integration, Data Migration and Business Intelligence/Artificial Intelligence solutions on Cloud (GCP/AWS/Azure). Ability to understand business requirements, translate them into functional and non-functional areas, define non-functional boundaries in terms of Availability, Scalability, Performance, Security, Resilience etc. Experience in architecting, designing, and implementing end to end data pipelines and data integration solutions for varied structured and unstructured data sources and targets. Experience of having worked in distributed computing and enterprise environments like Hadoop, GCP/AWS/Azure Cloud. Well versed with various Data Integration, and ETL technologies on Cloud like Spark, Pyspark/Scala, Dataflow, DataProc, EMR, etc. on various Cloud. Experience of having worked with traditional ETL tools like Informatica / DataStage / OWB / Talend , etc. Deep knowledge of one or more Cloud and On-Premise Databases like Cloud SQL, Cloud Spanner, Big Table, RDS, Aurora, DynamoDB, Oracle, Teradata, MySQL, DB2, SQL Server, etc. Exposure to any of the No-SQL databases like Mongo dB, CouchDB, Cassandra, Graph dB, etc. Experience in architecting and designing scalable data warehouse solutions on cloud on Big Query or Redshift. Experience in having worked on one or more data integration, storage, and data pipeline tool sets like S3, Cloud Storage, Athena, Glue, Sqoop, Flume, Hive, Kafka, Pub-Sub, Kinesis, Dataflow, DataProc, Airflow, Composer, Spark SQL, Presto, EMRFS, etc. Preferred experience of having worked on Machine Learning Frameworks like TensorFlow, Pytorch, etc. Good understanding of Cloud solutions for Iaas, PaaS, SaaS, Containers and Microservices Architecture and Design. Ability to compare products and tools across technology stacks on Google, AWS, and Azure Cloud. Good understanding of BI Reporting and Dashboarding and one or more tool sets associated with it like Looker, Tableau, Power BI, SAP BO, Cognos, Superset, etc. Understanding of Security features and Policies in one or more Cloud environments like GCP/AWS/Azure. Experience of having worked in business transformation projects for movement of On-Premise data solutions to Clouds like GCP/AWS/Azure. Be a trusted technical advisor to customers and solutions for complex Cloud & Data related technical challenges. Be a thought leader in architecture design and development of cloud data analytics solutions. Liaison with internal and external stakeholders to design optimized data analytics solutions. Partner with SMEs and Solutions Architects from leading cloud providers to present solutions to customers. Support Sales and GTM teams from a technical perspective in building proposals and SOWs. Lead discovery and design workshops with potential customers across the globe. Design and deliver thought leadership webinars and tech talks alongside customers and partners. Responsibilities Lead multiple data engagements on GCP Cloud for data lakes, data engineering, data migration, data warehouse, and business intelligence. Interface with multiple stakeholders within IT and business to understand the data requirements. Take complete responsibility for the successful delivery of all allocated projects on the parameters of Schedule, Quality, and Customer Satisfaction. Responsible for design and development of distributed, high volume multi-thread batch, real-time, and event processing systems. Implement processes and systems to validate data, monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it. Work with the Pre-Sales team on RFP, RFIs and help them by creating solutions for data. Mentor young Talent within the Team, Define and track their growth parameters. Contribute to building Assets and Accelerators.
Data Engineer (Azure) - Neoware Technology Solutions Private Limited Data Engineer (Azure) Requirements 4 - 10 years of hands-on experience in designing, developing and implementing data engineering solutions. Strong SQL development skills, including performance tuning and query optimization. Good understanding of data concepts. Proficiency in Python and a solid understanding of programming concepts. Hands-on experience with PySpark or Spark Scala for building data pipelines. Ensure data consistency and address ambiguities or inconsistencies across datasets. Understanding of streaming data pipelines for near real-time analytics. Experience with Azure services including Data Factory, Functions, Databricks, Synapse Analytics, Event Hub, Stream Analytics and Data Lake Storage. Familiarity with at least one NoSQL database. Knowledge of modern data architecture patterns and industry trends in data engineering. Understanding of data governance concepts for data platforms and analytical solutions. Experience with Git for managing version control for source code. Experience with DevOps processes, including experience implementing CI/CD pipelines for data engineering solutions. Strong analytical and problem-solving skills. Excellent communication and teamwork skills. Responsibilities Azure Certifications related to Data Engineering are highly preferred. Experience with Azure Kubernetes Service (AKS), Container Apps and API Management. Strong understanding and experience with BI/visualization tools like Power BI. Chennai, Bangalore Full time 4+ years Other positions Chennai / Bangalore / Mumbai 3+ years Principal Architect (Data and Cloud) Development
Data Engineer (AWS) - Neoware Technology Solutions Private Limited Data Engineer (AWS) Requirements 4 - 10 years of hands-on experience in designing, developing and implementing data engineering solutions. Strong SQL development skills, including performance tuning and query optimization. Good understanding of data concepts. Proficiency in Python and a solid understanding of programming concepts. Hands-on experience with PySpark or Spark Scala for building data pipelines. Understanding of streaming data pipelines for near real-time analytics. Experience with Azure services including Data Factory, Functions, Databricks, Synapse Analytics, Event Hub, Stream Analytics and Data Lake Storage. Familiarity with at least one NoSQL database. Knowledge of modern data architecture patterns and industry trends in data engineering. Understanding of data governance concepts for data platforms and analytical solutions. Experience with Git for managing version control for source code. Experience with DevOps processes, including experience implementing CI/CD pipelines for data engineering solutions. Strong analytical and problem-solving skills. Excellent communication and teamwork skills. Responsibilities Azure Certifications related to Data Engineering are highly preferred. Experience with Amazon AppFlow, EKS, API Gateway, NoSQL database services. Strong understanding and experience with BI/visualization tools like Power BI. Chennai, Bangalore Full time 4+ years Other positions Principal Architect (Data and Cloud) Development
As an AWS Data Engineer at Neoware Technology Solutions, a technology company based in Chennai, you will be responsible for optimizing Redshift database queries for enhanced performance, managing large table partitions, and utilizing AWS tools and services such as Glue, EMR, Athena, and StepFunction for data processing and management. Your role will involve developing and maintaining data pipelines, blending data using Python and SQL, and writing advanced code to support data engineering tasks. Additionally, you will apply your knowledge of visualization tools like Power BI and Tableau to create insightful data visualizations and collaborate closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions. To excel in this role, you should have advanced knowledge of Redshift database architecture, query optimization techniques, and performance tuning. Proficiency in AWS tools and services relevant to data engineering, such as Glue, EMR, Athena, and StepFunction is essential. Strong programming skills in Python for data manipulation, analysis, and automation, as well as mastery of SQL for data querying, manipulation, and optimization are required. Experience with visualization tools like Power BI or Tableau will be an advantage. In addition to technical skills, you should possess soft skills such as problem-solving abilities to identify and resolve complex data-related issues, effective communication skills to collaborate with stakeholders and document technical processes, strong analytical skills to analyze data and extract meaningful insights, meticulous attention to detail to ensure data accuracy and consistency, and flexibility to adapt to evolving technologies and data requirements. If you have 8 to 10 years of experience and are looking for a challenging opportunity to work in Chennai/Bangalore (Work from Office - 5 days), please reach out with your resumes to hr@neoware.ai.,
Development Machine Learning Engineer Requirements Develop predictive and prescriptive models to optimize business outcomes and drive growth Expert proficiency in Python Strong experience with PyTorch and scikit-learn Proficient with Git and GitHub Solid understanding and experience with Python unittest framework and Pytest for unit, integration, and API testing Hands-on experience with Dockerized deployment on AWS or Azure cloud platforms Experience with CI/CD pipelines using AWS CodePipeline or similar alternatives (e.g., Jenkins, GitLab CI) Experience with AWS or Azure services relevant to ML workloads (e.g., Sagemaker, EC2, S3, Azure ML, Azure Functions) Responsibilities Design, develop, and implement scalable machine learning models and algorithms to solve complex problems related to claims processing, fraud detection, risk stratification, member engagement, and predictive analytics within the payer landscape Collaborate closely with data scientists, product managers, and other engineering teams to translate business requirements into technical specifications and deliver end-to-end ML solutions Develop and optimize ML model training pipelines, ensuring data quality, feature engineering, and efficient model iteration Conduct rigorous model evaluation, hyperparameter tuning, and performance optimization using statistical analysis and best practices Integrate ML models into existing applications and systems, ensuring seamless deployment and operation Write clean, well-documented, and production-ready code, adhering to high software engineering standards Participate in code reviews, contribute to architectural discussions, and mentor junior engineers Stay abreast of the latest advancements in machine learning, healthcare technology, and industry best practices, actively proposing innovative solutions Ensure all ML solutions comply with relevant healthcare regulations and data privacy standards (e.g., HIPAA) Chennai Full time 5+ years Other positions Principal Architect (Data and Cloud) Chennai, Bangalore Full time 12-18 years
Job Title : Machine Learning Engineer Experience Level : 5 - 8 Years Location : Chennai About The Role We are seeking a highly skilled and experienced Machine Learning Engineer to join our innovative team within the U.S. healthcare payer sector. You will be instrumental in designing, developing, and deploying cutting-edge machine learning models that address critical business challenges, improve operational efficiency, and enhance member outcomes. This role demands a strong understanding of ML principles, robust software engineering practices, and familiarity with the unique complexities of healthcare data. Qualification Responsibilities : Design, develop, and implement scalable machine learning models and algorithms to solve complex problems related to claims processing, fraud detection, risk stratification, member engagement, and predictive analytics within the payer landscape. Collaborate closely with data scientists, product managers, and other engineering teams to translate business requirements into technical specifications and deliver end-to-end ML solutions. Develop and optimize ML model training pipelines, ensuring data quality, feature engineering, and efficient model iteration. Conduct rigorous model evaluation, hyperparameter tuning, and performance optimization using statistical analysis and best practices. Integrate ML models into existing applications and systems, ensuring seamless deployment and operation. Write clean, well-documented, and production-ready code, adhering to high software engineering standards. Participate in code reviews, contribute to architectural discussions, and mentor junior engineers. Stay abreast of the latest advancements in machine learning, healthcare technology, and industry best practices, actively proposing innovative solutions. Ensure all ML solutions comply with relevant healthcare regulations and data privacy standards (e.g., HIPAA). Required Technical Skills Programming Language : Expert proficiency in Python. Machine Learning Libraries : Strong experience with PyTorch and scikit-learn. Version Control : Proficient with Git and GitHub. Testing : Solid understanding and experience with Python unittest framework and Pytest for unit, integration, and API testing. Deployment : Hands-on experience with Dockerized deployment on AWS or Azure cloud platforms. CI/CD : Experience with CI/CD pipelines using AWS CodePipeline or similar alternatives (e.g., Jenkins, GitLab CI). Cloud Platforms : Experience with AWS or Azure services relevant to ML workloads (e.g., Sagemaker, EC2, S3, Azure ML, Azure Functions) (ref:hirist.tech)
Job Title : Data Engineer Experience Level : 5 - 8 Years Location : Chennai About The Role We are seeking a highly skilled and experienced Data Engineer to join our team, focusing on building and maintaining robust data pipelines and infrastructure for our U.S. healthcare payer operations. You will be responsible for the ingestion, transformation, and availability of large, complex healthcare datasets, enabling our data scientists and ML engineers to develop impactful solutions. This role requires a strong foundation in data warehousing, ETL/ELT processes, and cloud-based data platforms within a highly regulated : Design, develop, and optimize scalable data pipelines (ETL/ELT) to ingest, transform, and load diverse healthcare data from various sources into our data warehouse/lake. Build and maintain robust data models (e.g., star schema, snowflake schema) to support analytics, reporting, and machine learning initiatives. Write highly optimized SQL queries and Python scripts for data manipulation, cleansing, validation, and transformation. Ensure data quality, integrity, and reliability across all data pipelines. Collaborate with data scientists, ML engineers, and business stakeholders to understand data requirements and translate them into efficient data solutions. Implement and manage data governance policies, security measures, and access controls for sensitive healthcare data (e.g., HIPAA compliance). Monitor data pipeline performance, troubleshoot issues, and implement solutions for continuous improvement. Automate data workflows using orchestration tools and integrate with CI/CD pipelines. Contribute to the selection, evaluation, and implementation of new data technologies and tools. Document data pipelines, data models, and data flow processes thoroughly. Required Technical Skills Programming Language : Strong proficiency in Python for data processing and automation. Databases : Expert-level SQL skills for complex querying, data manipulation, and optimization. Experience with relational and NoSQL databases. Data Pipelines : Proven experience designing and implementing ETL/ELT processes. Cloud Platforms : Extensive hands-on experience with data services on Azure( Azure Data Lake, Azure Synapse Analytics, Azure Data Factory). Containerization : Familiarity with Docker for deploying data-related applications. Version Control : Proficient with Git and GitHub. Testing : Experience with Python unittest framework and Pytest for data pipeline testing. CI/CD : Understanding of CI/CD concepts and experience integrating data pipeline deployments with Azure Data Modeling : Strong knowledge of data warehousing concepts and data modeling techniques (ref:hirist.tech)
Job Title : Data Engineer Experience Level : 5 - 8 Years Location : Chennai About the Role : We are seeking a highly skilled and experienced Data Engineer to join our team, focusing on building and maintaining robust data pipelines and infrastructure for our U.S. healthcare payer operations. You will be responsible for the ingestion, transformation, and availability of large, complex healthcare datasets, enabling our data scientists and ML engineers to develop impactful solutions. This role requires a strong foundation in data warehousing, ETL/ELT processes, and cloud-based data platforms within a highly regulated : Design, develop, and optimize scalable data pipelines (ETL/ELT) to ingest, transform, and load diverse healthcare data from various sources into our data warehouse/lake. Build and maintain robust data models (e.g., star schema, snowflake schema) to support analytics, reporting, and machine learning initiatives. Write highly optimized SQL queries and Python scripts for data manipulation, cleansing, validation, and transformation. Ensure data quality, integrity, and reliability across all data pipelines. Collaborate with data scientists, ML engineers, and business stakeholders to understand data requirements and translate them into efficient data solutions. Implement and manage data governance policies, security measures, and access controls for sensitive healthcare data (e.g., HIPAA compliance). Monitor data pipeline performance, troubleshoot issues, and implement solutions for continuous improvement. Automate data workflows using orchestration tools and integrate with CI/CD pipelines. Contribute to the selection, evaluation, and implementation of new data technologies and tools. Document data pipelines, data models, and data flow processes thoroughly. Required Technical Skills Programming Language : Strong proficiency in Python for data processing and automation. Databases : Expert-level SQL skills for complex querying, data manipulation, and optimization. Experience with relational and NoSQL databases. Data Pipelines : Proven experience designing and implementing ETL/ELT processes. Cloud Platforms : Extensive hands-on experience with data services on AWS o (e.g., AWS S3, Redshift, Glue, EMR, Athena) Containerization : Familiarity with Docker for deploying data-related applications. Version Control : Proficient with Git and GitHub. Testing : Experience with Python unittest framework and Pytest for data pipeline testing. CI/CD : Understanding of CI/CD concepts and experience integrating data pipeline deployments with AWS CodePipeline or alternatives. Data Modeling : Strong knowledge of data warehousing concepts and data modeling techniques. (ref:hirist.tech)