Principal Solutions Architect
avantorsciences
Job Description
- 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)