Data Engineer Lead

Maintain and refactor existing Git/GitHub repositories, developing modular and reusable data components.

Implement CI/CD workflows for Databricks solutions, including promotion from development to controlled UAT environments.

Model marketing performance data including email events, campaign and promotion history, offers, packages, and tours.

Build point-in-time audience histories and connect marketing sends with downstream sales outcomes.

Develop data solutions at the person and household grain, using ID crosswalks and match rules based on existing identity resolution outputs.

Implement suppression and consent requirements, including Do Not Email rules, marketability flags, and PII handling.

Ingest and integrate data from SQL Server enterprise data warehouses and translate legacy SQL audience logic into governed definitions.

Deliver audiences from Databricks to Adobe Campaign or Segment, including service accounts, encryption, and auditing.

Profile unfamiliar data sources independently, producing data dictionaries and ERDs and verifying data availability and structure.

Develop data quality tests and validated query/result sets to support reliable datasets and agent evaluation.

Collaborate with analytics, engineering, marketing, data, and security teams to improve data solutions and processes.

Qualifications

5+ years of experience in Data Engineering or similar roles.

Hands-on experience developing data pipelines in Databricks, including Unity Catalog and Delta.

Strong hands-on experience with Python for data processing and transformation.

Strong SQL skills, including the ability to understand and translate complex existing SQL logic.

Experience with Git-based development and CI/CD, preferably using Databricks Asset Bundles or an equivalent approach.

Experience with Azure and promoting data solutions across development and controlled UAT environments.

Experience modeling data for marketing analytics, customer data, or similar business domains.

Experience with customer identity, person/household data, ID crosswalks, and identity matching rules.

Experience handling consent, suppression, marketability, and PII requirements.

Experience integrating data from SQL Server enterprise data warehouses.

Ability to independently profile unfamiliar data sources and document findings through data dictionaries and ERDs.

Strong analytical and problem-solving skills, with the ability to investigate ambiguous data issues independently.

Strong communication and collaboration skills for working with technical and business stakeholders.

What about languages?

You will need excellent written and verbal English for clear and effective communication with the team.

How much experience must I have?

In order to thrive in this role, you must have at least 5+ years of experience in data engineering or similar roles.

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.