Sr. Data Engineer

About Promtior

Promtior is at the forefront of the Agentic AI revolution, delivering cutting-edge solutions that transform businesses across industries — bridging technology and people to turn AI into a real competitive advantage. Since 2023, we've helped organizations boost operational efficiency through tailored Agentic AI solutions, from discovery and development to full implementation, across three core lines: AI Product Delivery (predictive analytics, intelligent automation, AI-driven chatbots, image processing), AI Department as a Service (LATAM-based teams that integrate directly with our clients' teams), and AI Adoption Consulting (helping companies find and act on AI opportunities across their business).
We're a team held together by genuine relationships, constant exchange, and shared learning. We believe innovation happens when people feel included and collaborate with purpose, and we aim for professional growth to go hand in hand with personal well-being.

About the Role

We're looking for a Data Engineer to join our Engineering team.

Key Responsibilities

You will own the design, construction, and evolution of scalable data pipelines in production environments, making architectural decisions on distributed data systems to guarantee performance, availability, and reliability at scale. You will define and evolve the cloud data storage strategy over Lakehouse-type architectures (Delta Lake / Unity Catalog), including partitioning, governance, and access models. You will design and lead the implementation of data quality frameworks, validations, and SLAs across domains, and establish CI/CD standards for data processes. You will define the observability and monitoring strategy for data pipelines,



lead the diagnosis and resolution of complex production incidents, and drive root cause analysis to prevent recurrence. You will act as a technical reference for engineering, product, and analytics teams, translating business needs into data architecture, and you will mentor mid-level and junior engineers through code reviews, technical guidance, and knowledge sharing. You will also lead continuous improvement initiatives in architecture, performance, and cost efficiency across the data platform.

Required Experience

- 5+ years of data engineering experience in production environments.

- Proven experience designing and operating distributed systems processing large volumes of data.

- Advanced experience with Databricks (Spark, Delta Lake, Workflows/Jobs, Unity Catalog), including job and cluster optimization (cluster tuning, Photon, Z-Ordering, partitioning).

- Strong development skills in Python (PySpark) and SQL for large-scale data processing.

- Experience owning data pipelines end to end, from design to production operation.

- Experience defining and implementing data quality controls or frameworks.

- Experience designing and maintaining CI/CD applied to data pipelines.

- Experience defining monitoring and observability strategies for data systems.

- Experience with Lakehouse architectures and Medallion patterns (Bronze/Silver/Gold), data modeling,



and Data Warehousing.

- Experience working in complex cloud environments (AWS, GCP, or Azure).

- Advanced debugging and troubleshooting skills in production incidents.

- Experience mentoring or providing technical guidance to other engineers.

- Advanced English Level.

- Experience with PySpark and Databricks job optimization (cluster tuning, Photon, Z-Ordering, partitioning).

- Experience with Lakehouse architectures and Medallion patterns (Bronze/Silver/Gold).

- Experience in data modeling and Data Warehousing.

- Experience optimizing large-scale data pipelines.

- Experience working in complex cloud environments (AWS, GCP, or Azure).

Especially Valued

- Experience with streaming and near real-time processing (Kafka, Spark Structured Streaming).

- Experience with orchestration and transformation tools (Airflow, dbt).

- Experience with Infrastructure as Code (Terraform) applied to data platforms.

- Experience with data governance, lineage, and cataloging at organizational scale.

- Experience optimizing cost and performance of large-scale data platforms (FinOps).

- Experience in regulated or high-volume environments (fintech, payments).

- Official certifications (Databricks Certified Data Engineer Professional, AWS, Azure, or GCP).

- Experience defining technical standards or participating in technical hiring.

Benefits

- 20 paid days off per year.

- Hybrid work model.

- Flex Days: monthly team activities.

- Professional development courses.

- Internal clubs (soccer, padel, running, cinema).

Location

Montevideo, Uruguay.
Córdoba, Corrientes or Chaco, Argentina.

· Hybrid work arrangement

📌 Sr. Data Engineer (Córdoba)
🏢 Promtior
📍 Córdoba