Forrester And Company - Cambridge, MA

posted 2 months ago

Full-time - Mid Level
Cambridge, MA
Merchant Wholesalers, Nondurable Goods

About the position

The Analytics Architect role at Forrester is designed for a talented individual who will collaborate with team members across the organization on various projects involving data lakehouse, CRM, and analytics systems. This exceptional candidate will play a crucial role in defining requirements and translating them into a high-performing, scalable architecture. As part of the architecture team, the individual will work hands-on with seasoned developers to bring these designs to life. In this role, the Analytics Architect will provide technical design and guidance for the development team, ensuring that business problems are effectively solved through collaboration with business stakeholders and developers. The architect will be responsible for designing and developing data pipelines and ETL processes to ingest and transform data, as well as creating end-to-end analytics solutions utilizing big data batch and stream processing frameworks such as Spark Structured Streaming and Kafka. Additionally, the architect will build and train machine learning models and leverage large language models (LLMs) to enhance analytics capabilities. Mentorship is also a key aspect of this role, as the architect will help train team members on best practices and architectural patterns. The position requires integration with RESTful web services to acquire data and provide access to analytics services, as well as the design and development of retrieval-augmented generation (RAG) applications that query structured data through text-to-SQL. This role is pivotal in driving innovation and ensuring that Forrester remains at the forefront of analytics and data architecture.

Responsibilities

  • Provide technical design and guidance for the development team.
  • Collaborate with business stakeholders and developers to solve business problems.
  • Design and develop data pipelines and ETL processes to ingest and transform data.
  • Design and develop end-to-end analytics solutions using big data batch and stream processing frameworks (e.g., Spark Structured Streaming, Kafka, etc.) and large language models (LLMs).
  • Build and train machine learning models and utilize large language models.
  • Help mentor and train team members on best practices and architectural patterns.
  • Integrate with RESTful web services to acquire data and provide access to analytics services.
  • Design and develop retrieval-augmented generation (RAG) applications that query structured data through text-to-SQL.

Requirements

  • A bachelor's degree in computer science or an equivalent technical field is desired.
  • Databricks Certified Data Engineer Professional or equivalent hands-on experience.
  • Five-plus years of programming experience with Python and SQL.
  • Five-plus years of experience with Apache Spark for data processing.
  • Five-plus years of experience building large-scale data pipelines with Apache Kafka and Spark stream processing.
  • Three-plus years of professional experience in a big data environment.
  • Three-plus years of hands-on experience with data modeling and performance tuning on Cassandra or other NoSQL database environment.
  • Hands-on experience developing genAI applications with frameworks such as LangChain and LangGraph.
  • Experience in designing and developing REST API integrations.
  • Experience with AWS architecture and employing services like Lambda functions, Athena, and S3.
  • Experience with the Databricks platform is a plus.
  • Strong problem-solving skills, including troubleshooting production systems.
  • Agile development experience and an understanding of how the architecture role succeeds in that process.
  • Solid communication and negotiation skills and the ability to express complex technical issues to a diverse audience (technical and nontechnical).

Benefits

  • Health insurance
  • Dental insurance
  • Vision insurance
  • 401k retirement plan
  • Paid holidays
  • Paid time off
  • Flexible scheduling
  • Professional development opportunities
  • Tuition reimbursement
  • Employee discount programs
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