Data Engineer
Blend360
full-time
Posted on:
Location Type: Remote
Location: Uruguay
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About the role
- Design and build production-grade data pipelines in Databricks using Spark/PySpark and SQL.
- Develop and maintain an Analytics ID stitching pipeline using deterministic and probabilistic matching techniques across multiple customer data sources.
- Build and manage modular data marts (Identity, Behavior, Demographics) with independent refresh cadences.
- Implement and maintain a scalable feature store supporting downstream analytics and data science use cases.
- Own the end-to-end data lifecycle: ingestion, transformation, validation, deployment, monitoring, and optimization.
- Develop data quality frameworks including schema drift detection, anomaly monitoring, match-rate validation, and automated deduplication audits.
- Implement CI/CD processes for multi-environment promotion (dev/staging/prod) in Databricks environments.
- Coordinate orchestration workflows and manage dependencies using Databricks Workflows or similar tools.
- Collaborate closely with Data Architects and Client stakeholders to translate business rules into scalable technical solutions.
- Produce comprehensive technical documentation including data contracts, lineage maps, architecture diagrams, and operational runbooks.
Requirements
- 4+ years of experience in Data Engineering building production-grade data pipelines at scale.
- Strong hands-on experience with Databricks and Apache Spark (PySpark preferred).
- Advanced SQL skills (complex joins, CTEs, window functions, performance tuning).
- Experience developing identity resolution or entity matching pipelines (deterministic and/or probabilistic).
- Experience designing and implementing data marts or dimensional models (Kimball or similar).
- Familiarity with data quality frameworks (schema drift detection, validation, anomaly monitoring).
- Experience implementing CI/CD for data pipelines and managing multi-environment deployments.
- Strong communication skills and ability to present technical concepts to non-technical stakeholders.
- Experience using Jira for ticket tracking and Confluence for documentation.
- Nice to Have: Experience with third-party data providers (Epsilon, LiveRamp, Neustar).
- Experience with feature stores (Databricks Feature Store, Feast, or similar).
- Knowledge of Databricks Unity Catalog.
- Experience managing large-scale customer data (transactions, loyalty, retail/QSR data).
- Experience with Delta Lake / Lakehouse architecture.
- Familiarity with orchestration tools such as Airflow.
- Experience working in consulting or embedded enterprise client environments.
- Advanced English level (written and spoken) required for client-facing collaboration and technical presentations.
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.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data engineeringdata pipelinesDatabricksApache SparkPySparkSQLdata quality frameworksCI/CDdata martsfeature stores
Soft Skills
communication skillspresentation skillscollaborationtechnical documentation