Bigquery Data Engineer

**Build, Scale & Operate Leading DTC Brands alongside A-Players***:
**Maneuver Marketing**

Our Vision, Mission & Success are fuelled by our commitment to be a driving force of positive change to the health of everyday consumers, providing conscious, high-quality & innovative supplement products.

In just 5 years, we kicked off our own DTC Health & Wellness brand from scratch and scaled it to USD$100M+ in annual sales, serving more than 3,000,000 customers worldwide with an average of 4,000 daily orders across 9 SKUs.

These results caught the attention of The Financial Times, as they ranked us among APAC top High-Growth Companies in 2023, and in 2024, we've been awarded 2nd place on the E50, jointly organised by The Business Times and KPMG in Singapore. This is just the beginning of our journey though, and you could be part of the next stage of our growth

**Your Next Role**:
We're looking for an experienced Data Engineer who can seamlessly integrate multiple marketing and eCommerce platforms with Google BigQuery, either through direct connections or using ETL tools.

You will play a critical role in helping us consolidate data streams, build reliable data pipelines, and ensure smooth data synchronization for our analytics and BI initiatives.

**Key Responsibilities**:

- Integrate key data sources (Shopify, Klaviyo, Zendesk, Stripe, PayPal, Meta Ads, Amazon Ads, Google Ads, etc.) into Google BigQuery via native connectors and custom pipelines (REST APIs, webhooks, SDKs).
- Evaluate, implement, and manage ETL tools (e.g., Fivetran, Airbyte, Stitch) where direct integrations are not available.
- Design and maintain scalable data models and schemas to support reporting, experimentation, and business use cases.
- Build, test, and document modular data transformation pipelines in dbt, ensuring reusability and adherence to best practices.
- Set up and manage workflow orchestration in Apache Airflow for scheduling, dependencies, retries, and alerting.
- Monitor and optimize data pipelines for performance, cost-efficiency, and data freshness.
- Implement automated data validation, anomaly detection, and logging to ensure high data reliability and integrity.
- Collaborate with analytics, marketing, and product teams to translate business needs into scalable and sustainable data solutions.
- Ensure compliance with data privacy regulations (e.g., GDPR, CCPA) by implementing access controls, encryption, and secure handling of PII.
- Support dashboarding and reporting tools (Looker, Power BI) by making modeled data accessible and trusted for stakeholders.
- Maintain clear, up-to-date documentation for all pipelines, data models, transformations, and security practices.

**Required Skills & Qualifications**:

- Proven experience with Google BigQuery and cloud-based data warehouse architectures (GCP preferred).
- Deep understanding of ETL/ELT processes, with hands-on experience using tools like Fivetran, Airbyte, Rivery, RudderStack, Portable.io, Windsor.ai, or similar.
- Proficient in building and maintaining custom data integrations using REST APIs, webhooks, and SDKs.
- Strong SQL expertise, including performance optimization and advanced querying for analytics workflows.
- Experience working with APIs from platforms such as Shopify, Klaviyo, Meta (Facebook/Instagram Ads), Google Ads, Amazon Ads, Recart, Postscript, Zendesk, Stripe, and PayPal.
- Skilled in data modeling and transformation using dbt (data build tool).
- Familiarity with orchestration tools like Apache Airflow for scheduling and monitoring workflows.
- Strong understanding of data privacy best practices and handling of sensitive data (e.g., PII) in compliance with GDPR/CCPA.
- Excellent problem-solving abilities, with a track record of debugging data issues and delivering scalable solutions.
- Effective collaboration and communication skills to work cross-functionally with analytics, product, and engineering teams

**Preferred Experience**:

- Previous experience integrating eCommerce and marketing tools.
- Certifications in Google Cloud Platform or BigQuery.

**Duration**:

- Project-based, with potential for ongoing collaboration based on performance.

If you're passionate about data integration and building scalable data infrastructures, we'd love to hear from you. Please provide examples of your previous integration projects, particularly those involving the platforms mentioned above.