Senior Data Engineer

This is a fully remote position, open to applicants in Argentina.

📋 Description

• Design and create scalable data pipelines to collect, transform, and organize data from APIs, databases, files, and event streams.

• Conduct technical design reviews and convert intricate business requirements into enterprise-level data solutions.

• Develop and enhance sophisticated data models (dimensional, data vault, domain-driven, canonical) to facilitate analytics, business intelligence, and productized datasets.

• Advocate for SDLC best practices, continuous delivery, and infrastructure automation through CI/CD and Infrastructure as Code.

• Optimize intricate distributed workloads utilizing SQL and Python; mentor team members on performance tuning and scalable design methodologies.

• Create reusable data frameworks, libraries, and reference architectures to enhance team efficiency and platform adoption.

• Conduct root-cause analysis for significant data incidents, lead long-term remediation efforts, and promote operational reliability enhancements.

• Offer technical guidance, oversee code reviews, and assist in advancing engineering capability maturity.

• Collaborate with Architects, Data Leads, Product Owners, and cross-functional engineering teams to establish long-term data strategies.

• Perform additional duties as needed.

⛳️ Requirements

• 5 to 7+ years of experience in data engineering or a similar technical domain.

• Proficiency in SQL and advanced skills in at least one programming language, preferably Python.

• Significant experience in designing and optimizing distributed data processing systems at scale.

• Demonstrated expertise in designing and implementing intricate data models across various business domains.

• Comprehensive knowledge of version control, CI/CD, DevOps/DataOps, automated testing, and engineering best practices.

• Capability to lead cross-functional engineering projects and influence technical roadmaps.

• Strong problem-solving, debugging, and analytical skills in complex, multi-system environments.

• Extensive practical experience in building scalable pipelines and workflows in Databricks (Delta Lake, Spark, Unity Catalog, Jobs, Workflows).

🏝️ Benefits

• Engagement Length: 12 months or more

• Time Zone: CST (9am - 5pm)

• Laptop: BYOD.

• Overtime Required: Very unlikely. In the rare event that some "on call" hours are requested during the week, the overtime rate is 1.5x the regular rate.