Senior Data Engineer

Apply Digital

. Work with internal disciplines, vendors, clients, and stakeholders to define data requirements and technology stacks .

Posted 10/26/2026full-timeSantiago • ChileSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data engineering with a strong focus on SQL, ELT/ETL processes, and cloud data warehousing, particularly using Snowflake and dbt. Proven ability to translate business requirements into technical specifications and optimize data architectures for performance and security.

Highest-signal resume keywords

Expert-Level SQLHands-On Snowflake ExperienceStrong Hands-On dbt ExperienceExperience with ELT/ETL ProcessesExperience Integrating Data with Customer Engagement Platforms

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringDimensional Data ModellingSemantic Data ModellingData Migration PlanningData Security Best PracticesData Architecture FrameworksData Pipeline DevelopmentData Analysis TechniquesTroubleshooting Data IssuesData Documentation

Soft Skills

Excellent Communication SkillsProblem-Solving Skills

Tools & Technologies

SnowflakeDbtGitAWSGCPBrazeSalesforce Marketing CloudSailthruDockerKubernetes

Certifications & Qualifications

Snowflake (SnowPro) CertificationDbt CertificationCloud Certifications

Industry Keywords

Data PrivacyData SecurityCustomer Data ModellingDigital ProductsData Warehousing

Tech Stack

Tools & technologies

AWSCloudDockerETLGoogle Cloud PlatformKubernetesPySparkPythonSnowflakeSparkSQL

About the role

Key responsibilities & impact

Work with internal disciplines, vendors, clients, and stakeholders to define data requirements and technology stacks
Audit CRM and marketing source systems and define migration guidelines
Translate business requirements into technical specifications covering data streams, integrations, transformations, databases, and data warehouses
Design and build dbt transformation layers on Snowflake, including identity resolution, semantic, and consumption/reporting layers
Build and maintain pipelines activating data in customer engagement platforms such as Braze
Audit digital products and produce data foundation recommendations
Work in git-based workflows with code review, dbt tests, and CI/CD processes
Define data architecture frameworks, standards, and principles
Analyze and optimize architectures and models for performance and cost
Plan activities to populate new solutions with current and historical data
Implement data security and access controls
Document data sources, ELT/ETL processes, data dictionaries, metadata, lineage, and data flows
Research and recommend technologies and develop data management, security, and privacy best practices

Requirements

What you’ll need

Bachelor's degree in Computer Science, Information Systems, or a related field
At least 5 years of experience in data engineering or related fields
Expert-level SQL
Strong experience in ELT/ETL and cloud data warehousing
Hands-on Snowflake experience
Strong hands-on dbt experience, including modelling, tests, documentation, and macros
Experience with git-based workflows, branching, code review, and CI/CD
Proven experience in dimensional and semantic data modelling and analysis techniques
Experience with customer data modelling and identity resolution across CRM, marketing, and product sources
Experience integrating data with customer engagement platforms such as Braze, Salesforce Marketing Cloud, or Sailthru
Experience planning data migrations between platforms
Working knowledge of Python for data tooling and automation
Working knowledge of AWS or GCP and their data services
Ability to troubleshoot data issues and develop effective solutions
Ability to produce written guidelines and recommendations for client and third-party teams
Understanding of data privacy and security best practices
Excellent communication and problem-solving skills
Fluent English
Snowflake (SnowPro), dbt, or cloud certifications are nice to have
Spark/PySpark, Docker, Kubernetes, and consumer or digital-product data experience are nice to have

Benefits

Comp & perks

Agentic Delivery: opportunities to broaden skills across engagements with international brands
Inclusive and safe work environment
Generous training budgets and mentorship focused on Agentic AI and future-of-work skills
Generous vacation policy
Flexible work arrangements, including remote, in-office, and blended work
Equal opportunity and inclusive workplace commitment
Recruitment accommodations