Senior Analytics Engineer

Aimpoint Digital

Senior Analytics Engineer developing end-to-end analytical solutions and working with various clients. Partnering with stakeholders to improve processes and derive data-driven insights.

Posted 4/11/2026full-timeRemote • 🇺🇸 United StatesSeniorWebsite

Tech Stack

Tools & technologies

Amazon RedshiftAWSAzureBigQueryCloudETLGoogle Cloud PlatformInformaticaMatillionPythonSparkSQLTableau

About the role

Key responsibilities & impact

Become a trusted advisor working together with our clients, partnering with data owners, analysts, business users, and executive stakeholders to translate business needs into scalable analytics solutions
Work independently as part of a small team to solve complex analytics engineering use-cases across a variety of industries
Design and develop the analytical layer, including curated data models, semantic layers, metrics definitions, and transformation pipelines that power reporting, dashboards, self-service analytics, and AI use cases
Work with modern tools such as Snowflake, Databricks, Fivetran, and dbt and credentialize your skills with certifications
Write high-quality code in SQL, Python, and Spark, and use software engineering tools and best-practices such as Git and CI/CD
Contribute to best practices around analytics engineering - data modeling, metric standardization, data quality, and governance
Accelerate analytics development velocity and improve solution quality by using AI-assisted engineering workflows and tools such as Codex, Claude, Copilot, and platform-native assistants like Snowflake Cortex Code and Databricks Genie Code
Partner closely with data engineers, analysts, data scientists to support production-grade analytics and AI applications

Requirements

What you’ll need

Degree educated in Computer Science, Engineering, Mathematics, or equivalent experience
Experience with managing stakeholders and collaborating with customers
Strong written and verbal communication skills required
3+ years working with relational databases and query languages, with deep expertise in SQL
3+ years of data modeling experience, including dimensional modeling, star schema, entity-relationship design, and analytics-focused modeling best practices
3+ years building data pipelines in production, with the ability to work across structured, semi-structured and unstructured data
3+ years writing clean, maintainable, and robust code in SQL and/or Python
2+ years' experience with dbt Core and/or dbt Cloud required
Ability to manage an individual workstream independently
Expertise in software engineering concepts and best practices, including version control, testing, documentation, and CI/CD
Experience working with cloud data warehouses (Databricks, Snowflake, Google BigQuery, AWS Redshift, Microsoft Synapse) preferred
Experience working with other cloud ETL/ELT tools (Fivetran, Matillion, Informatica, Talend, etc.) preferred
Experience working with cloud platforms such as AWS, Azure, or GCP preferred
Experience defining metrics, semantic layers, and reusable business logic for analytics consumption preferred
Familiarity with modern BI and visualization platforms such as Power BI, Tableau, or Sigma preferred
Experience enabling or accelerating analytics engineering workflows with AI tools such as Codex, Claude, Copilot, Snowflake Cortex Code, and/or Databricks Genie Code preferred
Consulting experience strongly preferred.

Benefits

Comp & perks

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Hard Skills & Tools

SQLPythonSparkdata modelingdimensional modelingstar schemaentity-relationship designdata pipelinesCI/CDanalytics engineering

Soft Skills

stakeholder managementcollaborationwritten communicationverbal communicationindependent workproblem-solvingconsulting