Principal Solutions Architect – Data and Advanced Analytics

The Opportunity: Education: Bachelor’s or Master’s degree in computer science, Data Science, or a related field. Experience: 15+ years of experience in data architecture roadmaps, data modeling, and database design, data engineering, building data pipelines, ETL processes, business analytics, data science, software development, data modeling or data engineering work and distributed data systems with at least 3 years in a leadership or principal architect role. Strong technical knowledge for designing and implementing data integration & migration, data management, data analytic & reporting solutions. Experienced in implementing some machine learning techniques (may include supervised and unsupervised learning, deep learning, natural language processing, ensemble methods, dimensionality reduction) Skilled in programming languages like Python, R, SQL, and experience in working with data visualization tools like Tableau and Power BI. Experienced in implementing Snowflake for data engineering and data science. Experienced in implementing enterprise data management architecture and solutions. Hands-on expertise in Cloud Data technologies (Databricks, Microsoft OneLake/Fabric, Snowflake, AWS or GCP) Expertise in ETL tools (Matillion, Fivetran, SAP BODS, Snowpipe, Informatica or similar tools), ETL/Data integration/Streaming – Talend, DataBricks, Python, Spark, Kafka Exposure to real-time data processing and streaming technologies such as Kafka, Spark Current deep experience with AWS, APIs, accelerators, DevSecOps Enterprise Data Catalog tools including Collibra, Alation Expert knowledge of Power BI tool Proficient in DAX, M, SQL, with the ability to write complex and optimized queries Exposure to LLMs, MLs including Supervised, Unsupervised, Regression, Classification, NN, Clustering, SVM, Recommender Systems, NLP etc is a plus Experience in Python ML Libraries like - Pandas, Numpy, Scipy, Matplotlib, NLTK etc. & Open-Source ML Stack TensorFlow, Keras etc SAP functional domain knowledge is big plus (Supply Chain, Finance etc.) Strong programming skills in languages such as SQL, Python, C#, Spark, and/or R. Utilize architectural methods and standards to design secure application integrations and data provisioning methodologies for reporting and analytics. Experience in data governance, data security, data mesh, fabric, lakehouse, data compliance etc. Relevant certifications in AWS, Azure, and enterprise architecture (e.g., AWS Certified Solutions Architect Associate, Azure Fundamentals, Azure Data Fundamentals, TOGAF). Strong knowledge of data modeling, database design, and ETL processes. Ability to assist in the architecture and development of a DevSecOps, CI/CD analytics development pipeline environment using in-house and cloud-based technologies. Excellent communication and presentation skills with the ability to present complex data insights to both technical and non-technical audiences. Strong analytical skills with the ability to collect, organize, analyze, and disseminate insights with attention to detail and accuracy. Good team player, able to manage multiple assignments, and adapt to changing client needs. Skilled in implementing advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) Familiarity with machine learning frameworks (like Keras or PyTorch), libraries (like scikit-learn), and data science platforms (like Databricks and SageMaker) Who you are Expert in data warehousing, data lakes, and data governance, data integration, Business Intelligence and analytics, AI and automation capabilities. Possess deep understanding of Master Data, Data Quality, and related best practices. Works with the Senior leadership within Technology and Business to develop architecture priorities and direction to enable business imperatives Displays strong thought leadership in pursuit of modern architecture principals and technology modernization Have proven experience with Cloud Technologies, notably AWS and Azure. Hands-on expert with modern data tools and platforms such as Databricks, Snowflake, Alation, and Collibra. Develops data-driven solutions to unusually complex business challenges. Experience in programming languages such as Scala, Python, or similar Have a strong background in AI/ML technologies and integrating them with data platforms. Are experienced in data modeling, data warehouse design, data analytics design, and complex data migrations. Exceptional problem-solver and with a keen attention to detail. Excellent communicator and collaborator. Demonstrated leader in guiding data strategy in a growing organization. Certified in AWS, Azure, Databricks, Snowflake, or similar platforms a plus. Prior experience in life sciences or supply chain domain a plus How you will create an impact Architect, design, and develop data platforms and solutions that are scalable, reliable, and performant. Lead the design and implementation of robust data pipelines and ETL processes. Drive the strategy and implementation for data warehousing, data lakes, and data governance. Define data strategies, and leverage the latest technologies in data handling and data analytics. Ensure high-quality data architecture, including adherence to Master Data and Data Quality best practices. Oversee design of data models and designs required to implement performant Microsoft BI /Tableau/Qlik/SAP Reporting Solutions Collaborate with AI/ML teams to prepare and model application data for downstream analytical needs. Research, recommend, and integrate new data technologies and tools as needed. Collaborate with cross-functional teams to ensure that data solutions are aligned with company needs and architectural best practices. Provide mentorship to junior data engineers and architects, promoting a culture of continuous learning and innovation. Advocate for best practices in cloud technologies, ensuring efficient use and optimal performance in both AWS and Azure environments. Design of all aspects of data solutions including modeling, developing, technical documentation, data diagrams and data dictionaries. Lead development and execution of data solutions involving domain specific analytics. Provide expertise in the development of standards, architectural governance, design patterns, and practices, evaluate best applicable solutions for different use cases. Work cross-functionally with product owners, business stakeholders, and management. Suggest how to design and optimize data architecture for consumption, utilization, and analytics on the Data Warehouse Analyze data patterns and optimize data processing. Suggest best practice, technology, and process improvements. Comfortable with rapid prototyping and disciplined software development processes. Realize and communicate trends related to Data technologies. Disclaimer: The above statements are intended to describe the general nature and level of work being performed by employees assigned to this classification. They are not intended to be cons