Analytics Data Engineer-REMOTE

Invesp is a job website that connects professionals with remote opportunities, including roles such as Analytics Data Engineer. The platform focuses on providing flexible work arrangements, allowing candidates to explore positions from various industries without geographic constraints. While specific details about the company's industry, size, or client base are not provided, the presence of remote job listings suggests an emphasis on digital transformation and scalable workforce solutions. Invesp likely operates within the broader talent acquisition and employment services sector, supporting individuals seeking remote work options. The website serves as a hub for job seekers to discover roles that align with their skills and career goals, offering a streamlined approach to finding meaningful employment in a distributed work environment.

About Us: Invesp is a conversion rate optimization agency that helps e-commerce and lead generation businesses grow their conversion rates and revenue through research, experimentation and analytics. Our clients rely on us for data they can trust, and this role sits at the heart of that. About the Role: We are looking for a hands-on Analytics Engineer to join our analytics team. You will own the health of our clients' tracking and data: finding what is broken, understanding why, and fixing it properly. This is not a ground-up architecture role. Our clients already have their stacks in place. Your job is to audit them, spot tracking glitches, explain data variance and discrepancies between platforms, and get the numbers back to a state everyone can rely on. You will work across GA4, GTM (client side and server side), BigQuery, Shopify, HubSpot, Triple Whale, Meta and Google Ads etc. You will also write BigQuery SQL to answer analysis questions and support our reporting. You may be required to walk the clients through tracking plans you have built. What you will do: Audit and debug GA4 and GTM implementations, including server-side containers, and fix broken or duplicated tracking Investigate discrepancies between GA4, Shopify, HubSpot, Triple Whale, Meta and Google Ads, and document the root cause Implement and troubleshoot cross-domain, subdomain and subdirectory tracking so sessions and cookies stay intact Implement and fix cookie consent setups, including Consent Mode v2 and CMP integrations, through GTM or directly in code Maintain Meta Pixel and Conversions API, and Google Ads conversion tracking and enhanced conversions Set up and maintain integrations into BigQuery and write SQL to pull insights from GA4 export data Make code changes where tracking needs them, in JavaScript, data layer implementations or site templates Write tracking plans and occasionally present them to clients Minimum requirements: 3 to 5 years of hands-on experience in analytics implementation or analytics engineering Strong GA4 and GTM experience, including server-side GTM Strong BigQuery SQL, including working with the GA4 export schema (nested and repeated fields, UNNEST) Solid JavaScript, plus Python for data work Practical experience with cookie consent implementation and privacy regulations such as GDPR and CCPA Experience with Meta and Google Ads conversion tracking Clear written English and the ability to explain a technical problem to a non-technical client Our ideal candidate: Has worked with Shopify and HubSpot data, and ideally Triple Whale Has used ETL or ELT tools such as Fivetran, Stitch or Airbyte, and product analytics tools such as Amplitude or Mixpanel Enjoys chasing down why two numbers do not match Works independently, documents what they fix, and is comfortable with a globally distributed team Has agency or multi-client experience Some of your key metrics include: Time to diagnose and resolve tracking issues Accuracy of data across client platforms after fixes Quality and clarity of tracking plans and documentation Turnaround on BigQuery analysis requests Show more

The Analytics Data Engineer role involves designing and maintaining data pipelines to support analytical processes. This position requires expertise in data integration and transformation to ensure accurate insights for business decision-making.