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Sr. Data Engineer

1 week ago
Mexico, Argentina, Brazil, Chile, Colombia, Costa Rica, Uruguay
Contract
Senior
Data Engineer
Software Development
Agile Apache Spark AWS CI/CD Databricks Git Kafka Machine Learning Python SQL
Apply Now
Resilient Co

Resilient Co

Resilient Co is a technology consulting company that empowers businesses with smart solutions and diverse teams, offering resilient support in the dynamic tech industry.

Professional Services
11-50
Founded 2020
View All Jobs 8

Description

  • Design, build, and support scalable data pipelines that ingest, transform, and curate data from APIs, databases, files, and event streams.
  • Lead technical design reviews and translate complex business needs into enterprise-grade data solutions.
  • Develop and optimize advanced data models to support analytics, BI, and productized datasets.
  • Champion SDLC best practices, continuous delivery, and infrastructure automation using CI/CD and Infrastructure as Code.
  • Optimize distributed workloads using SQL and Python, and mentor others on tuning and scalable design patterns.
  • Build reusable data frameworks, libraries, and reference architectures to improve team productivity and platform adoption.
  • Perform root-cause analysis for major data incidents and drive long-term remediation and reliability improvements.
  • Provide technical mentorship, guide code reviews, and help improve engineering maturity.
  • Collaborate with architects, data leads, product owners, and cross-functional engineering teams on long-term data strategy.
  • Perform other duties as assigned.

Requirements

  • 5 to 7+ years of experience in data engineering or a related technical field.
  • Expertise in SQL and advanced proficiency in at least one programming language, with Python preferred.
  • Strong experience designing and tuning distributed data processing systems at scale.
  • Proven experience designing and implementing complex data models across multiple business domains.
  • Strong knowledge of version control, CI/CD, DevOps/DataOps, automated testing, and engineering best practices.
  • Ability to lead cross-functional engineering initiatives and influence technical roadmaps.
  • Strong problem-solving, debugging, and analytical skills in complex, multi-system environments.
  • Extensive hands-on experience building scalable pipelines and workflows in Databricks, including Delta Lake, Spark, Unity Catalog, Jobs, and Workflows.
  • DataOps experience, including pipeline observability, monitoring, and automated quality, is preferred.
  • Knowledge of metadata management or cataloging platforms such as Purview, Collibra, or Alation is preferred.
  • Experience with streaming frameworks used with Spark Structured Streaming, such as Kafka, Event Hubs, or Kinesis, is preferred.
  • Experience working in an Agile environment is preferred.
  • Engagement length of 12 months or more.
  • Availability to work CST hours, 9am to 5pm.
  • BYOD laptop required.

Benefits

  • Overtime is very unlikely.
  • If on-call hours are required during the week, overtime is paid at 1.5x the regular rate.
  • Long-term engagement of 12 months or more.

Interested in this position?

Apply directly on the company website

Apply Now

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