About The Position

Avalara is hiring a Customer Solutions Technical Implementation Engineer to accelerate complex customer solutions for property tax and help turn repeatable implementation patterns into scalable product features. You'll partner with our Solutions team on data-heavy custom builds for enterprise customers, and with Product/Engineering to productize what works into maintainable, configurable capabilities. This is a hands-on technical role. You are strongest in databases, data modeling, and integration engineering. You are fluent using modern AI-assisted developer tools, such as Cursor, Copilot, and ChatGPT. You will report to the General Manager for Property Tax. You can work remote. Avalara is an AI-first Company AI is embedded in our workflows, decision-making, and products. Success here requires embracing AI as an essential capability. You’ll bring experience using AI and AI-related technologies, ready to thrive here. You’ll apply AI every day to business challenges - improving efficiency, contributing solutions, and driving results for your team, our company, and our customers. You’ll grow with AI by staying curious about new trends and best practices, and by sharing what you learn so others can benefit too. What You Need To Know About Avalara We’re defining the relationship between tax and tech. We’ve already built an industry-leading cloud compliance platform, processing over 54 billion customer API calls and over 6.6 million tax returns a year. Our growth is real - we're a billion dollar business - and we’re not slowing down until we’ve achieved our mission - to be part of every transaction in the world. We’re bright, innovative, and disruptive, like the orange we love to wear. It captures our quirky spirit and optimistic mindset. It shows off the culture we’ve designed, that empowers our people to win. We’ve been different from day one. Join us, and your career will be too.

Requirements

  • 5+ years in a hands-on technical role such as Technical Implementation Engineer, Integration Engineer, or similar.
  • Deep SQL and relational database expertise.
  • Experience building and operating production-grade data pipelines/integrations (ELT/ETL, APIs, or file-based ingestion) with reliability patterns (retries, monitoring, reconciliation).
  • Capability building and debugging modern integrations using APIs (REST) orGraphQL, including auth (OAuth2/API keys), pagination, rate limiting, and error handling.
  • Hands-on experience using AI-assisted developer tools (e.g., Cursor, GitHub Copilot, ChatGPT/enterprise assistants) to deliver engineering output—paired with validation habits.
  • Translate ambiguous domain requirements into technical solutions and validate correctness end-to-end.
  • Write design docs and explain tradeoffs across Solutions, Product, and Engineering.
  • Experience in complex/rules-heavy domains (e.g., tax, finance, compliance, ERP, healthcare, payments).
  • Experience with modern cloud data platforms (e.g., Snowflake, Postgres, SQL Server, BigQuery).
  • Familiarity with transformation/orchestration tooling (e.g., dbt, Airflow, Azure Data Factory, Fivetran, Informatica, SSIS).
  • Python for automation (data validation, integration glue, internal tooling).
  • Experience with API contract tooling and testing (OpenAPI/Swagger, Postman/Insomnia, automated API tests).
  • Comfort working in engineering workflows (Git, PRs, CI/CD, logging/observability).

Responsibilities

  • Lead technical discovery for data-intensive implementations: source systems, data structures, integration constraints, validation requirements, edge cases.
  • Develop database-layer deliverables: schemas, transformations, views, stored procedures/functions, migration scripts, and performance improvements.
  • Build and troubleshoot integrations (API and file-based ingestion), including idempotency, retries, monitoring, and reconciliation.
  • Create reusable implementation assets: templates, reference architectures, runbooks, validation checklists, and repeatable "starter kits" for the Solutions team.
  • Identify repeatable patterns across custom builds and propose product improvements.
  • Translate implementation insights into clear technical specs: requirements, recommended design, tradeoffs, acceptance criteria, and test strategy.
  • Build prototypes/POCs (SQL plus optional Python) to validate approaches and de-risk engineering investments.
  • Define data quality and regression checks to ensure new capabilities remain correct as they scale.
  • Use AI-enabled developer tools (e.g., Cursor/Copilot/ChatGPT) to speed up creation of: database scripts and migrations transformation logic and mapping utilities integration code and connector scaffolding validation/reconciliation harnesses implementation and technical documentation
  • Apply disciplined verification practices (tests, reconciliations, peer review, logging) to ensure AI-generated outputs meet production standards.

Benefits

  • In addition to a great compensation package, paid time off, and paid parental leave, many Avalara employees are eligible for bonuses.
  • Benefits vary by location but generally include private medical, life, and disability insurance.
  • Avalara strongly supports diversity, equity, and inclusion, and is committed to integrating them into our business practices and our organizational culture. We also have a total of 8 employee-run resource groups, each with senior leadership and exec sponsorship.
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