Job Description
Design, implement, and maintain complex data pipelines, ensuring scalability and reliability using Airflow, dbt, Rivery, Python, and SQL, enabling robust ingestion and transformation of structured and semi-structured data
Serve as a strategic partner to business teams, working closely with stakeholders to translate high-level goals into data solutions that support forecasting, performance tracking, and optimization
Develop and maintain clean, well-documented data models in Snowflake and BigQuery that support analytics, reporting, and operational workflows and contribute to architecture decisions
Integrate data from a variety of internal and external sources, including Google Analytics and third-party APIs, to support full-funnel visibility across departments
Enable self-service analytics by ensuring data assets are discoverable and usable via tools such as Tableau, including thoughtful semantic layer design and performance tuning
Contribute to the development of robust monitoring and observability practices for data quality and pipeline health
Collaborate on architecture and design decisions, including cloud infrastructure and containerization using AWS. Pulumi and Docker
Maintain strong documentation and promote engineering standards that ensure transparency, maintainability, and reusability of data systems
150-170k
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Required Skills & Experience
7+ years of professional experience in data engineering, analytics engineering, or related roles.
Advanced proficiency in SQL and Python, with expertise in efficient query writing, data structures, and software engineering principles.
Hands-on experience with Snowflake and/or Big Query, including data modeling and performance optimization.
Proficiency with orchestration tools (e.g., Airflow) and data integration tools like dbt.
Experience working with cloud platforms, especially AWS, for data storage, compute, and infrastructure management, including services such as AWS Batch, ECR, Lambda functions, and related tools.
Familiarity with data analytics and visualization tools, particularly Tableau, and ability to support data consumers in building actionable dashboards.
Experience with marketing and product data sources, including Google Analytics and similar platforms.
Strong knowledge of ETL/ELT design and data warehousing solutions.
Familiarity with CI/CD pipelines and DevOps practices for data engineering.
Strong skills in Microsoft Suite for documentation and collaboration.
Robust experience with API design and integration.
Familiarity with SCRUM development methodologies and tools like Jira
Nice to Have Skills & Experience
Jewelry experience
Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.