Analytics Engineer II

TAXWELL•Haverford, PA

About The Position

Taxwell is seeking a detail-oriented, results-driven Analytics Engineer II to join its Data Analytics Engineering team. The role builds and maintains reliable, scalable, well-documented data models that support reporting, self-service analytics, and business decision-making across the organization. The engineer collaborates with data engineers, analysts, data scientists, and business stakeholders to turn raw data into clean, reusable datasets and consistent metrics. The position independently delivers well-defined analytics solutions within established architectural patterns and partners with senior engineers on more complex technical decisions. The team uses modern cloud data technologies and AI-assisted development tools to improve development, testing, troubleshooting, and documentation.

Requirements

3–5 years of experience in analytics engineering, data modeling, business intelligence, or a related data role.
Strong SQL skills, including complex joins, window functions, aggregations, query troubleshooting, and optimization.
Hands-on dbt experience, including modular models, testing, documentation, and basic Jinja.
Experience with Snowflake or a comparable cloud data warehouse.
Working knowledge of dimensional modeling, dataset grain, and table relationships.
Experience using Git, pull requests, and collaborative code review workflows.
Understanding of data quality, automated testing, documentation, governance, and data lineage principles.
Ability to independently deliver well-defined work, clarify ambiguous requirements, and troubleshoot data issues.
Experience using AI-assisted development tools such as Cursor, Claude Code, GitHub Copilot, or similar technologies.
Ability to communicate technical concepts effectively to technical and non-technical audiences.
Attention to detail, curiosity, and a proactive approach to problem-solving.

Nice To Haves

Experience with semantic layers, shared metric definitions, or data contracts.
Experience with modern BI tools such as Sigma, Omni, Tableau, Power BI, or Looker.
Familiarity with data ingestion and integration tools such as Fivetran or Matia.
Familiarity with CI/CD workflows and automated deployment of analytics code.
Experience with Python for scripting or automation.
Familiarity with AWS services used for data integration and processing.

Responsibilities

Design, build, and maintain data models and transformation pipelines using dbt and Snowflake within established architectural patterns.
Develop and optimize SQL queries and transformations for reporting, analytics, and operational needs.
Own assigned work from requirements gathering through development, validation, deployment, and ongoing support.
Collaborate with business stakeholders to clarify requirements and translate analytical needs into accurate, well-structured datasets and metrics.
Partner with data engineers to integrate new data sources and troubleshoot upstream dependencies.
Develop and maintain dbt models, macros, automated tests, and documentation using modular, reusable practices.
Investigate and resolve data quality issues, troubleshoot transformation failures, and improve query and model performance.
Contribute to shared metric definitions and semantic layers to support consistent reporting across business units and analytics tools.
Maintain data definitions, documentation, and lineage to support governance and self-service analytics.
Participate in code reviews and knowledge-sharing, applying team standards and providing constructive feedback.
Use AI-assisted development tools for SQL development, troubleshooting, testing, and documentation, validating generated code and results before use.
Communicate progress, dependencies, and risks clearly, and seek guidance when complexity or ambiguity requires additional support.