Job Description
We are seeking a talented Data Engineer to join our growing data team as the third dedicated engineer. You will own end-to-end scope for critical data initiatives in a Google Cloud environment, accelerating our work in social marketing analytics.
Our focus is on social marketing data—including influencer performance, organic social media, social listening, paid media, and related metrics—to power influencer programs, AI-driven social marketing content generation, social listening/monitoring, and advanced reporting. The data pipelines and infrastructure you build will enable analysts to access timely, high-quality data, supercharge their workflows, expand into new data sources, and deliver actionable insights for marketing teams (including supporting downstream Marketing Mix Modeling (MMM) efforts by partner teams).
While we collaborate with external teams on MMM builds, direct MMM modeling experience is not required—our priority is robust data foundations.
You will work alongside two experienced Data Engineers, owning independent streams of work while contributing to team-wide pipeline and modeling efforts.
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/.
Skills and Requirements Mid-to-senior level experience as a Data Engineer (or comparable role) with proven ability to own end-to-end data solutions.
Strong hands-on expertise in Google Cloud Platform, especially BigQuery for warehousing, querying, and optimization.
Familiarity with the broader Google Cloud data suite (e.g., Dataflow, Pub/Sub, Cloud Composer/Airflow, Cloud Storage, Vertex AI or other AI integrations) and experience implementing AI-enhanced workflows in GCP.
Proficiency in Python (primary) for scripting, ETL logic, and data processing; some JavaScript experience is a plus.
Advanced SQL skills for complex querying, modeling, and performance tuning (especially in BigQuery).
Domain experience working with social marketing data, including:
Influencer marketing datasets
Organic social media metrics
Social listening / monitoring data
Paid media performance data
Understanding of marketing metrics needs and how to structure data to support analytics, reporting, and AI use cases in social channels.
Experience building reliable, scalable pipelines in modern cloud data environments; comfort with both pipeline engineering and light modeling is valued (common in today’s data roles).
Ability to accelerate existing underway work by quickly ramping up on our tools and stack.
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Our focus is on social marketing data—including influencer performance, organic social media, social listening, paid media, and related metrics—to power influencer programs, AI-driven social marketing content generation, social listening/monitoring, and advanced reporting. The data pipelines and infrastructure you build will enable analysts to access timely, high-quality data, supercharge their workflows, expand into new data sources, and deliver actionable insights for marketing teams (including supporting downstream Marketing Mix Modeling (MMM) efforts by partner teams).
While we collaborate with external teams on MMM builds, direct MMM modeling experience is not required—our priority is robust data foundations.
You will work alongside two experienced Data Engineers, owning independent streams of work while contributing to team-wide pipeline and modeling efforts.
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/.
Skills and Requirements Mid-to-senior level experience as a Data Engineer (or comparable role) with proven ability to own end-to-end data solutions.
Strong hands-on expertise in Google Cloud Platform, especially BigQuery for warehousing, querying, and optimization.
Familiarity with the broader Google Cloud data suite (e.g., Dataflow, Pub/Sub, Cloud Composer/Airflow, Cloud Storage, Vertex AI or other AI integrations) and experience implementing AI-enhanced workflows in GCP.
Proficiency in Python (primary) for scripting, ETL logic, and data processing; some JavaScript experience is a plus.
Advanced SQL skills for complex querying, modeling, and performance tuning (especially in BigQuery).
Domain experience working with social marketing data, including:
Influencer marketing datasets
Organic social media metrics
Social listening / monitoring data
Paid media performance data
Understanding of marketing metrics needs and how to structure data to support analytics, reporting, and AI use cases in social channels.
Experience building reliable, scalable pipelines in modern cloud data environments; comfort with both pipeline engineering and light modeling is valued (common in today’s data roles).
Ability to accelerate existing underway work by quickly ramping up on our tools and stack.
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