Data Engineer Lead

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com  

We are looking for a Data Engineer Lead to design, build, and govern the cloud data layer that powers analytics, reporting, and AI-driven applications using the Snowflake platform. This role focuses on modeling unified customer data from multiple source systems, building reliable ingestion and transformation pipelines, and making governed, well-documented datasets available to downstream teams and applications. 

The ideal candidate has strong experience with cloud data warehousing, production data pipelines, and data modeling for both analytics and machine learning consumption. Experience working across marketing, engagement, and third-party data sources, and collaborating with technical and business stakeholders to deliver governed data products. This role also carries ownership of end-to-end integration testing, so comfort with data validation and quality assurance is essential. 

Responsibilities 

• Design and build a unified, flattened data model that consolidates customer, content, and engagement data from multiple source systems into a single governed source of truth, supported by a documented data dictionary. 

• Implement and validate identity resolution logic, populating and reconciling customer identifiers across systems to defined match-rate thresholds without duplicate or orphaned keys. 

• Onboard third-party data sets, including consumer attribute providers, with schema validation, refresh governance, and automated quality checks. 

• Normalize content metadata and consumer attributes to consistent naming, value, and timestamp standards so that downstream analytics and AI agents can consume data without bespoke transformation code. 

• Build structured gold layers from raw engagement platform events, including customer engagement platforms, enabling self-serve reporting beyond native platform lookback limits. 

• Develop closed-loop measurement pipelines that ingest campaign performance data from advertising and CDP platforms into the warehouse, and expose it through self-serve analytics views. 

• Own end-to-end integration testing and support the user acceptance testing cycle, building and maintaining the integration test suite across all critical workstreams. 

• Apply data governance requirements in practice, including PII handling, privacy regulation compliance, and documented access control mapping. 

• Collaborate with engineering, AI, analytics, and business teams to translate requirements into governed, reusable data products. 

Required Skills: 

• Strong hands-on experience with Snowflake, including data modeling, performance tuning, resource governance, and role-based access control. 

• Advanced SQL and strong Python, with experience building and maintaining production ELT and data transformation pipelines. 

• Experience with dimensional and flattened data modeling for analytics and machine learning or AI application consumption. 

• Experience with data quality and validation frameworks, and comfort taking ownership of integration testing and QA activities. 

• Working knowledge of data governance practices, including PII handling, privacy compliance, and access control design. 

• Ability to work independently, take ownership of technical initiatives, and deliver in a fast-paced delivery environment. 

Nice-to-Have Skills 

• Experience with identity resolution and entity matching across multiple source systems. 

• Experience with marketing and advertising technology data ecosystems 

• Experience working with media, streaming, or audience data at scale. 

• Experience preparing and structuring datasets consumed directly by LLM-based agents or conversational analytics tools. 

• Familiarity with modern data engineering practices such as data contracts, observability, and CI/CD for data pipelines. 

Our Perks and Benefits: 

📚 Learning Opportunities: 

• Certifications in AWS (we are AWS Partners), Databricks, and Snowflake. 

• Access to AI learning paths to stay up to date with the latest technologies. 

• Study plans, courses, and additional certifications tailored to your role. 

• Access to Udemy Business, offering thousands of courses to boost your technical and soft skills. 

• English lessons to support your professional communication. 

🛫 Travel opportunities to attend industry conferences and meet clients. 

👩‍🏫 Mentoring and Development: 

• Career development plans and mentorship programs to help shape your path. 

🎁 Celebrations & Support: 

• Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones. 

• Company-provided equipment.  

⚖️ Flexible working options to help you strike the right balance.    

Other benefits may vary according to your location in LATAM. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters.