Senior Analytics Engineer

Soostone; New York (NY); Hybrid; USD 90,000 - 140,000; Full time

Job summary

An innovative software technology company is seeking a Senior Analytics Engineer to transform raw data into high-quality datasets that drive AI solutions. This role emphasizes collaboration with data scientists and engineers to design robust data models and transformation logic. You'll work on complex data projects, ensuring data accuracy and reliability while optimizing data pipelines. Join a forward-thinking team that values analytical skills and offers opportunities to apply cutting-edge AI methodologies in real-world applications. If you're passionate about data and eager to make an impact, this role is perfect for you.

Qualifications

• 3+ years of experience in data transformation and building pipelines.
• Expert-level proficiency in SQL for complex data manipulation.
• Experience with data quality frameworks and processes.

Responsibilities

• Design and maintain scalable data transformation pipelines using SQL.
• Collaborate with stakeholders to define data requirements.
• Mentor junior team members on best practices in data modeling.

Skills

Data Transformation

SQL

Data Modeling

Data Quality Frameworks

Communication Skills

Education

Bachelor's in Computer Science

Bachelor's in Statistics

Bachelor's in Mathematics

Tools

dbt

Napkin

Tableau

Looker

Job description

Position Title: Senior Analytics Engineer

Location: New York City preferred, with a hybrid 4-day in-office policy. Remote work is possible within the United States for experienced candidates with demonstrated ability to collaborate effectively in a remote setting.

Company Overview:

Soostone is a software technology company focused on optimizing AI solutions with extensive experience deploying machine learning into real-world operational workflows. We work with clients where our proprietary technology can produce an outsized impact by leveraging state-of-the-art AI methodologies in commercial circumstances. Our work involves a variety of challenging subjects, including large-scale data processing, predictive, causal, and optimizing models, domain-specific languages, modern machine learning toolkit, data visualization, highly concurrent systems, and several adjacent topics.

Role Overview:

As a key Data Science team member, you will collaborate closely with data scientists, ML engineers, software engineers, and business stakeholders. Your primary focus will be transforming raw data into meaningful, high-quality datasets that power our internal R&D and client-facing AI solutions. This role is centered on data transformation logic, ensuring data accuracy, and building robust data models, rather than heavy infrastructure management.

Contact: [e-mail]

Position Summary:

We seek a Senior Analytics Engineer with a strong aptitude for understanding and shaping data. You will take ownership of complex data transformation projects, driving the design, development, and optimization of data models and transformation logic using SQL-centric tools. This role requires deep engagement with real-world data, translating business requirements into effective data structures, and ensuring the reliability and quality of the resulting datasets. While the core focus is on data transformation and modeling, there will be opportunities to apply broader data analysis skills to enhance our analytical solutions.

Key Responsibilities:

• Design, develop, and maintain robust and scalable data transformation pipelines, primarily using SQL and our internal framework, Napkin.
• Develop, optimize, and troubleshoot complex SQL queries to ensure efficient and accurate data manipulation, aggregation, and extraction.
• Define and implement data models, schemas, and semantic layers to give structure and meaning to raw data sources.
• Develop analytical logic, including formulas, derivations, and classifications, leveraging various numerical methods to extract insights from complex datasets.
• Implement and monitor data quality checks and processes to ensure data accuracy, completeness, and consistency throughout the pipeline.
• Implement and monitor drift management systems, ensuring consistency between training and real-time inference in our ML systems.
• Pursue data pipeline efficiency and cost optimization opportunities
• Collaborate directly with clients and internal stakeholders to understand data sources, map raw data to business concepts, and define data requirements.
• Work closely with Data Scientists and ML Engineers to understand their data needs and provide them with reliable, well-structured datasets for modeling.
• Mentor junior team members on best practices for data modeling, SQL development, and data transformation techniques.
• Contribute to discussions on data architecture improvements, focusing on scalability, efficiency, and maintainability of data transformation workflows.
• Become a subject matter expert in specific data domains and our preferred technology stack (SQL, Napkin).

Qualifications & Key Skills:

• 3+ years of experience focused on data transformation, data modeling, and building data pipelines, with a strong emphasis on SQL.
• Expert-level proficiency in SQL for complex data manipulation, aggregation, and analysis. Must have internalized entirely advanced SQL concepts like window functions and CTEs.
• Significant hands-on experience with dbt or similar SQL-based data transformation tools (e.g., Dataform, internal frameworks like Napkin).
• Proven ability to translate business requirements into effective data models and transformation logic.
• Strong communication and collaboration skills to work effectively with technical and non-technical stakeholders.
• Experience in establishing and maintaining data quality frameworks and processes.
• Experience working directly with client data and mapping data processing to real-world business scenarios is highly desirable.
• Expertise in data visualization and business intelligence tools like Tableau and Looker will be viewed as a distinct advantage.
• Familiarity with data warehousing concepts (e.g., dimensional modeling) and database technologies.
• Exposure to broader data science concepts or experience working closely with data science teams is a plus.
• A highly analytical educational background (e.g., Computer Science, Statistics, Economics, Engineering, Mathematics) and demonstrated critical thinking skills.
• Excellent problem-solving skills and the ability to independently own and drive complex data projects.
• Use of GenAI / Language Models: Our team follows a dual path of expectation, where we expect you to have outstanding analysis, problem-solving, and synthesis skills you bring into every effort, while also deriving maximum additional value from language models we make available to our team members.