William Blair - Chicago, IL

posted 2 months ago

Full-time - Mid Level
Chicago, IL
Securities, Commodity Contracts, and Other Financial Investments and Related Activities

About the position

The Information Technology team at William Blair is on a mission to become a true business partner, and we are seeking a Senior AI Engineer to help execute this vision. This role involves building end-to-end AI solutions that leverage both proprietary and third-party data sources to drive business growth and achieve productivity gains. The ideal candidate will have a passion for problem-solving, building innovative solutions, and delivering actionable, data-driven insights in a fast-paced and dynamic environment. As a Senior AI Engineer, you will be responsible for developing and deploying robust data architectures, including data lakes and data warehouses, to manage large-scale datasets while ensuring data quality and integrity. You will implement Microservices architecture to facilitate the scalable and efficient management of our data services. Additionally, you will leverage and refine open-source generative AI models to solve advanced data augmentation and analytics challenges. Your role will also involve managing and optimizing data processing workflows to ensure timely and accurate data availability, as well as optimizing data retrieval processes through database tuning and query optimization. You will analyze both structured and unstructured data to gain insights into customer interactions with our products and services, and collaborate with data scientists, analysts, and business teams to deliver scalable data solutions. Furthermore, you will work closely with IT, security, and compliance teams to ensure adherence to data management and protection standards, while managing and optimizing cloud-based data solutions, preferably on Azure. Your responsibilities will include maintaining comprehensive documentation of data models, pipelines, and ETL processes, ensuring the robustness, scalability, and sustainability of our data infrastructure in the cloud environment.

Responsibilities

  • Develop and deploy robust data architectures (data lake, data warehouse, etc.) to handle large-scale datasets, ensuring data quality and integrity.
  • Develop and implement Microservices architecture to facilitate the scalable and efficient management of our data services.
  • Leverage and refine open-source generative AI models and use existing generative AI models to solve advanced data augmentation and analytics.
  • Manage and optimize data processing workflows, ensuring timely and accurate data availability.
  • Optimize data retrieval processes through database tuning, query optimization, and ensuring scalable infrastructures.
  • Analyze structured and unstructured data to understand how our customers interact with our product and service offerings.
  • Perform the design, analysis, and interpretation of projects from data requirement gathering to data processing, modeling, and recommendations.
  • Work with data scientists, analysts, and business teams to understand data requirements and deliver scalable data solutions.
  • Collaborate with IT, security, and compliance teams to ensure adherence to data management and protection standards.
  • Manage and optimize cloud-based data solutions (preferably Azure: including Synapse, Azure Machine Learning, Databricks, ADF, and Azure Data Lake).
  • Ensure robustness, scalability, and sustainability of data infrastructure in the cloud environment.
  • Maintain comprehensive documentation of data models, pipelines, and ETL processes.

Requirements

  • Master's degree in Computer Science, Engineering, Data Science, or a related field.
  • 5+ years of experience as a data engineer or machine learning engineer, with a proven track record in developing ETL processes, data pipeline architecture, and machine learning model development.
  • Strong proficiency in Python for data processing and manipulation.
  • Experience with SQL and Spark to handle data extraction, transformation, and loading of big data.
  • Demonstrable expertise in designing and implementing efficient data models to support ETL processes and data analytics.
  • Extensive experience managing and optimizing Azure cloud data technologies (Synapse, Databricks, ADF, or Azure Data Lake).
  • Hands-on experience with API utilization, development, and management.
  • Practical experience with event-driven architecture and real-time data processing.
  • Ability to effectively communicate technical concepts to both technical and non-technical stakeholders.
  • Experience with data analysis and statistical modeling using the Python ecosystem, with packages such as numpy, pandas, statsmodels, scikit-learn, etc.
  • Experience working with various machine learning / deep learning algorithms and frameworks.
  • Self-starter, comfortable with ambiguity, ability to initiate and drive projects with minimal oversight and guidance.
  • A record of continuous learning and adaptation to stay updated with the latest in data engineering, machine learning, generative AI, cloud technologies, and data compliance standards.
  • Certifications in Azure Data Engineering, Azure Machine Learning, Spark, or other relevant technologies.
  • Proven track record of leveraging data to deliver business value and present data-driven insights to business audiences.
  • Familiarity with PowerBI for developing interactive reports and data visualizations.
  • Experience with LLMs and OpenAI APIs.
  • Experience shipping code into production.
  • Experience in the investment banking or financial sector.

Nice-to-haves

  • Experience with data governance and compliance standards.
  • Familiarity with additional cloud platforms beyond Azure, such as AWS or Google Cloud.
  • Knowledge of data visualization tools beyond PowerBI, such as Tableau or Looker.

Benefits

  • Health insurance coverage
  • Dental insurance coverage
  • 401k retirement savings plan
  • Flexible scheduling options
  • Professional development opportunities
  • Paid holidays
  • Employee discount programs
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