Senior Data Engineer

Resilient Co.

Senior Data Engineer at Resilient Co. designing and building data pipelines.

Posted 7/11/2026contractRemote • 🇦🇷 ArgentinaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building scalable data pipelines, optimizing complex data models, and implementing CI/CD practices. Proven ability to lead cross-functional teams and mentor others in data engineering best practices.

Highest-signal resume keywords

Data Engineering ExperienceSQL ProficiencyPython ProgrammingCI/CD ImplementationDatabricks Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DesignData ModelingDistributed Data ProcessingRoot-Cause AnalysisDebugging Skills

Soft Skills

Problem-SolvingAnalytical SkillsMentorship

Tools & Technologies

DatabricksDelta LakeSparkUnity CatalogVersion Control

Industry Keywords

SDLC Best PracticesInfrastructure AutomationDataOpsEngineering Best PracticesCross-Functional Collaboration

Tech Stack

Tools & technologies

PythonSDLCSparkSQLUnityVault

About the role

Key responsibilities & impact

Design and build scalable data pipelines to 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 (dimensional, data vault, domain-driven, canonical) to support analytics, BI, and productized datasets.
Champion SDLC best practices, continuous delivery, and infrastructure automation using CI/CD and Infrastructure as Code.
Optimize complex distributed workloads using SQL, Python; mentor others on tuning and scalable design patterns.
Build reusable data frameworks, libraries, and reference architectures to accelerate team productivity and platform adoption.
Perform root-cause analysis for major data incidents, lead long-term remediation, and drive operational reliability improvements.
Provide technical mentorship, guide code reviews, and help shape engineering capability maturity.
Collaborate with Architects, Data Leads, Product Owners, and cross-functional engineering teams to define long-term data strategies.
Perform other duties as assigned.

Requirements

What you’ll need

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, 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 (Delta Lake, Spark, Unity Catalog, Jobs, Workflows).

Benefits

Comp & perks

Engagement Length: 12 months or more
Time Zone: CST (9am - 5pm)
Laptop: BYOD.
Overtime Required: Very unlikely. In the unlikely event that they ask for some "on call" hours during the week the OT rate is 1.5x the regular rate