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What are some common challenges faced by professionals working remotely with Google BigQuery, and how can they be addressed?

One common challenge remote Google BigQuery professionals face is optimizing query performance while managing cost, since inefficient queries can quickly increase expenses. Collaboration with distributed teams can also be tricky, especially when aligning on data schema changes or troubleshooting issues across time zones. To address these, it's helpful to establish clear documentation practices, use version control for SQL scripts, and schedule regular check-ins with team members. Leveraging Google BigQuery's built-in monitoring and cost control tools also helps maintain project efficiency and budget constraints.

What is the difference between Remote Google Bigquery vs Remote Data Analyst?

AspectRemote Google BigqueryRemote Data Analyst
Required CredentialsSQL, Cloud certifications, Google Cloud certificationsSQL, Data analysis, Excel, sometimes certifications
Work EnvironmentCloud platforms, data warehouses, remote teamsData visualization tools, spreadsheets, reporting platforms
Industry UsageData engineering, cloud services, analyticsBusiness intelligence, reporting, insights

Remote Google Bigquery specialists focus on managing and querying large datasets using Google Cloud, requiring technical skills and cloud certifications. Remote Data Analysts interpret data, create reports, and provide insights, often using visualization tools. While both roles work remotely and handle data, Bigquery roles are more technical and cloud-focused, whereas Data Analysts focus on analysis and reporting.

What are the key skills and qualifications needed to thrive as a remote Google BigQuery specialist?

To excel as a Remote Google BigQuery Specialist, you need a solid background in SQL, data warehousing concepts, and experience with cloud-based analytics platforms, typically supported by a degree in computer science or a related field. Familiarity with Google Cloud Platform (GCP), BigQuery ML, data visualization tools like Looker or Tableau, and relevant certifications such as Google Professional Data Engineer are highly beneficial. Strong problem-solving skills, attention to detail, and effective remote communication set top performers apart. These skills and qualifications enable efficient management of large datasets, insightful analytics, and seamless collaboration in distributed teams.

What is a remote Google BigQuery?

A Remote Google BigQuery job is a position where professionals manage, analyze, and optimize large datasets using Google BigQuery, a fully-managed cloud data warehouse, while working from a location outside of a traditional office. These roles typically involve writing SQL queries, building data pipelines, and collaborating with data engineers and analysts to derive insights from data stored in the cloud. Remote BigQuery specialists may also be responsible for maintaining data security, optimizing query performance, and integrating BigQuery with other data tools. This flexible setup allows employees to work from anywhere with a stable internet connection while supporting organizations' data needs.
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Remote Google Bigquery jobs near you

Associate Director, Paid Search (Feeds & Shopping) (Remote)

Monks

Detroit, MI • Remote

Other

Re-posted 14 days ago

Job description

About the Role

We're looking for an Associate Director of Paid Search who lives and breathes the commerce side of search - someone who sees a product feed not as plumbing but as the single highest-leverage asset in a retail or DTC media program.

This is a hands-on leadership role. You'll own the strategy and execution of large Shopping and Performance Max programs, obsess over feed quality and structure, and connect paid search to the broader buying experience - from query to PDP to conversion. You'll lead a small group of search/shopping specialists while staying close enough to the platforms to spot what others miss.

Responsibilities:
  • Own paid search strategy across Google Ads and Microsoft Advertising for a portfolio of commerce-driven clients, with Shopping, Performance Max, and standard search working as one system.
  • Treat feed optimization as a core discipline: audit, restructure, and continuously improve product feeds (titles, attributes, GTINs, custom labels, supplemental feeds) to maximize coverage, relevance, and ROAS.
  • Participate in new business pitches.
  • Architect campaign and feed segmentation strategies that give buyers control inside increasingly automated, AI-driven products.
  • Partner with clients and internal teams on the full shopping experience - landing pages, PDP quality, merchant feed health, promotions, and conversion tracking - so media spend lands on a page that converts.
  • Set the measurement frame: ROAS, new-customer acquisition, margin-aware bidding, incrementality, and feed-level performance diagnostics.
  • Lead, mentor, and grow a team of search and feed specialists; raise the bar on QA, hygiene, and documentation.
  • Stay ahead of platform changes - Performance Max evolution, AI Max, retail media adjacencies, and the shift toward signal- and feed-driven buying - and translate it into client roadmaps.
  • Act as a senior point of contact for clients: present strategy, defend recommendations with data, and build trust.
About YouThe essentials:
  • 7+ years in paid search / performance media, with deep, demonstrable experience in Shopping and feed-driven campaigns at meaningful spend.
  • Genuine feed fluency - you've worked directly with Merchant Center, feed management tools (e.g., Feedonomics, Versafeed, Productsup, or similar), and know how feed structure drives auction outcomes.
  • Strong command of Google Ads (Shopping, Performance Max, search) and ideally Microsoft Advertising and retail media platforms.
  • A commerce mindset: comfort with margin, AOV, LTV, and the mechanics of how a feed connects to a storefront.
  • Experience leading people and owning client relationships at a senior level, ideally in an agency or managed-service environment.
  • Excellent communication and the ability to make complex feed/search strategy legible to non-specialist stakeholders.
Not a must, but a plus:
  • Experience with large catalogs (retail, marketplace, multi-region) and supplemental feed strategies.
  • Familiarity with retail media networks (Amazon, Walmart Connect, Instacart) as part of an integrated commerce program.
  • Scripting/automation exposure (Google Ads scripts) to scale feed and account management.
  • Analytical rigor - comfortable in GA4, BigQuery, Looker Studio, or similar, and able to turn data into a clear point of view.

At Monks, we believe in fostering an environment where a diversity of perspectives can thrive. We proactively work to design hiring processes that promote equity and inclusion while mitigating bias. We celebrate diversity and are committed to building a team that reflects the communities we serve. We welcome and encourage qualified applicants, from all backgrounds, who are excited to contribute to our mission.  

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