Data Engineer

at  Keystone Strategy

QUALIFICATIONS

• 5+ years experiences working on data analysis, data science, ETL/ELT on large datasets
• 2-3 years’ progressive experience architecting cloud-based solutions on one of the major cloud provider platforms (AWS/GCP/Azure)
• 2-3 years’ experience in leading data teams preferred
• Advanced proficiency working with data analysis languages (Python, R, SQL)
• Advanced proficiency working with machine learning libraries and tools (Pytorch, Keras, TensorFlow, Transformers, NLTK, scikit-learn, OpenAI API, etc)
• Experience with data orchestration tools (Airflow, dbt, Prefect, Luigi, etc.) and data modeling patterns
• Big data platform experience (Snowflake, Spark, BigQuery, etc.)
• Solid knowledge of the Software Development Lifecycle principles and interest in applying to a fast-paced, data-focused role
• Experience with version control (git) workflows
• Capacity to work within complex systems and large data sets
• Prior experience at a matrix-based organization or consulting firm is a plus
• Experience with CI/CD pipelines is required
• Broad knowledge of AI/ML/NLP/CV/AR concepts
• Experience with LLM model training, finetuning, evaluation. And Implementation such as vector databases, RAG, etc.
• Experience with GCP,AWS, or Azure cloud services. Specifically experience with data services, lambda functions, Bedrock/Vertex AI, etc.
• A desire to be a part of and help grow a great team and organization
• The passion to learn, grow, and help us to improve our business
• Bachelor’s degree; Ability to quickly adapt to new technologies
  US Salary Range: $150,000 - $180,000, plus an annual discretionary bonus, 401k contribution, and competitive benefits package. Actual compensation within the range will depend upon the level the individual is hired into based on their skills, experience, qualifications.
  At Keystone we believe diversity matters. At every level of our firm, we seek to advance and promote diversity, foster an inclusive culture, and ensure our colleagues have a deep sense of respect and belonging. If you are interested in growing your career with colleagues from varied backgrounds and cultures, consider Keystone Strategy.

As a Data Engineer, you will be responsible for architecting and driving the design and implementation of our data infrastructure and systems, and addressing various data engineering, data science, software development needs of our client-facing teams with data-driven approaches. Your expertise in data engineering will play a pivotal role in enabling data-driven solutions and empowering our team of analysts and consultants.

Your responsibilities will include:

• Evaluate client needs, propose suitable recommendations, and carry out tailored implementation for various practices and projects. Such as devising strategic approaches for litigation support or product delivery for the CoreAI team
• Consult with client-facing teams and client stakeholders to design and architect data infrastructure to automate manual processes, optimize data delivery and processing, and ensure user experience
• Responsible for managing project big data requests and challenges by building reproducible data ingestion pipelines and downstream analytic processes to derive value for the teams
• Develop custom software solutions such as APIs to interact with large language models or end-user portals to search through high volumes of data easily
• Leverage the appropriate infrastructure required for optimal extraction, transformation, and loading (ETL/ELT) of data from a wide variety of data sources using SQL and ‘big data’ technologies
• Lead creation, maintenance, and implementation of in-house tools, libraries, and systems to increase the efficiency and scalability of the team
• Build tools and APIs to deploy data science and machine learning systems at scale on projects
• Lead the adoption of best practices in data engineering and software development
• Work closely with cross-functional teams of engagement managers, product managers, and consultants to identify areas of opportunity and value