Sr. Data Engineer

Resilientco; Argentina; Presencial; ARS 103.231.134 - 176.967.658; Jornada completa

Descripción de la vacante

Resilientco is seeking a Senior Data Engineer to design, build, and support core data platform systems that empower fast, data-driven decisions. You will develop scalable pipelines, data models, and governance tooling, collaborating with business partners and the Data Platform team to enable advanced analytics and ML use cases.

We value reliability, hands-on leadership, and a passion for scalable, observable data infrastructure that accelerates product teams.

Formación

• 5–7+ years of data engineering or related field.
• Expertise in SQL and Python.
• 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.
• Hands-on experience with Databricks (Delta Lake, Spark, Unity Catalog, Jobs, Workflows).

Responsabilidades

• 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.

Conocimientos

SQL

Python

Distributed data processing

Data modeling

Version control

CI/CD

DevOps/DataOps

Databricks

Delta Lake

Spark

Unity Catalog

Jobs

Workflows

Kafka

Data catalogs

Herramientas

Databricks

Spark

Delta Lake

Unity Catalog

Kafka

Purview

Collibra

Alation

Descripción del empleo

Summary

As a Senior Data Engineer, you will design, build, and support the core systems that power our data platform to enable fast, data-driven decisions. You will create scalable data pipelines, self-service tools, and governance solutions that ensure trusted, accessible data across the organization. Working closely with business partners and the Data Platform team, you will support advanced analytics and machine learning use cases while sharing knowledge to elevate the team.
This role emphasizes scalable pipeline development, distributed data processing, strong data modeling, and engineering best practices. Success requires curiosity, experimentation, and a commitment to operational reliability and team mentorship.

Responsibilities

• 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

• 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).

Nice to Have

• DataOps experience (pipeline observability, monitoring, automated quality).
• Knowledge of metadata management or cataloging platforms (Purview, Collibra, Alation).
• Experience with streaming frameworks used with Spark Structured Streaming (Kafka, Event Hubs, Kinesis).
• Experience working in an Agile environment.