Data Engineer Databricks

[Only Argentina, Chile, Uruguay, Perú, Colombia]
RequirementsQUALIFICATIONS:EDUCATION AND/OR EXPERIENCEBachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related field, plus a minimum of 3 years of data engineering experience, including hands-on work on production data pipelines.In lieu of a degree, a combined 7 years of higher education and/or relevant work experience, including at least 3 years in data engineering.CERTIFICATES, LICENSES, REGISTRATIONSDatabricks Certified Data Engineer Associate (or equivalent) preferred.COMPETENCIES (SKILLS AND ABILITIES)– Strong verbal and written communication skills, with the ability to convey technical concepts to both technical and non-technical audiences.– Proficient SQL — window functions, MERGE/upsert patterns, and incremental processing.– Proficiency in Python for data ingestion, orchestration, and pipeline tooling.– Hands-on experience with Apache Spark and Delta Lake (or comparable distributed/lakehouse technology).– Solid understanding of dimensional modeling (facts, dimensions, slowly-changing dimensions) and broader data-modeling fundamentals.– Experience building and maintaining batch and/or incremental pipelines, including monitoring and troubleshooting.– Understanding of architectural trade-offs — when to favor batch, incremental, or streaming approaches, and how each balances data freshness, latency, cost, and operational complexity.– Willingness to collaborate, share knowledge, and grow toward greater technical ownership.– Working experience with Databricks (declarative pipelines / Delta Live Tables, serverless SQL warehouses, Unity Catalog, job orchestration) preferred.– Exposure to streaming and event-driven architectures (e.g., Kafka) is a plus.– Familiarity with Terraform / Infrastructure-as-Code is a plus.– Experience supporting BI/reporting consumers (e.g., Power BI, embedded customer-facing reports) and turning business rules into trustworthy metrics is a plus.– Domain experience with transactional, point-of-sale, invoicing, financial, or animal-health data is a plus.
Professional CredentialsA Databricks Certified Data Engineer Associate credential or a comparable industry certification is highly desirable.
Core CompetenciesTechnical Communication: Excellent written and oral skills with the capacity to explain complex technical topics to diverse audiences.Advanced SQL & Python: Mastery of SQL (including MERGE patterns and window functions) and proficiency in Python for pipeline orchestration and data ingestion.Data Architecture: Practical experience with Apache Spark, Delta Lake, and Lakehouse technologies, alongside a firm grasp of dimensional modeling and SCD strategies.Pipeline Operations: Proven ability to build, monitor, and troubleshoot batch and incremental pipelines while evaluating architectural trade-offs between cost, latency, and complexity.Job responsibilities
ESSENTIAL DUTIES AND RESPONSIBILITIES: – Build and maintain ingestion pipelines from source systems into the lakehouse, across both batch and streaming patterns.– Contribute to decisions about the platform’s processing strategy — weighing batch vs. incremental vs. streaming approaches against freshness requirements, cost, and operational complexity.– Develop and optimize silver- and gold-layer transformations using declarative ETL — including SCD Type 1 and Type 2 handling, fact and dimension tables, incremental merge logic, and change-detection strategies.– Translate business logic into reusable, well-tested pipeline components.– Contribute to platform infrastructure as code and the CI/CD path that deploys it.– Follow and help uphold engineering standards — code review, testing, observability, and operational runbooks.– Investigate and resolve performance, cost, and data-quality issues across the pipeline, escalating complex trade-offs as needed.– Collaborate with senior engineers, stakeholders, and downstream consumers to support data contracts and SLAs.– Support the onboarding of new data sources as the platform scales.