Senior Data Engineer
Backend Developer
Marketing
Senior
Application Support
Big Data
Bigdata
Business Systems
Cloud
Cloud Data Warehouse
Cloud Data Warehouse
Cloud Native
Cloud Operations
Cloud Platform
Cloud Platforms
CRM
Crm Analytics
Crm Integration
Data
Data Analysis
Data Analytics
Data Architecture
Data Build Tool
Data Engineer
Data Engineering
Data Integration
Data Integration Tools
Data Management
Data Modeling
Data Operations
Data Pipeline
Data Pipelines
Data Platform
Data Processing
Data Transforms
Data Warehouse
Data Warehousing
Database
Databases
Dbt
Engineer
ETL
Google Cloud
Informatica
Information Technology (IT)
Integration
Marketing Automation
Marketing Cloud
Marketing Technology
Programming Languages
Pyspark
Salesforce
Salesforce Crm
Snowflake
Software
Software Development
Spark
SQL
Job Description
APPLY is building modern data foundations for customer engagement, and you will help shape how data moves from source systems into cloud warehouses and activation pipelines. This hybrid/remote-friendly role supports an inclusive, safe environment with AI and strategic upskilling, agentic delivery practices, and a generous vacation policy alongside flexible work arrangements.
Responsibilities
- Partner with internal teams, vendors, clients, and stakeholders to define data requirements and the technology stack for projects.
- Audit source systems across CRM and marketing platforms (including Salesforce and Sailthru) and define migration guidelines for what to migrate, the target structure, and execution order for internal or third-party delivery.
- Translate business needs into technical specifications covering data streams, integrations, transformations, and the data warehouse.
- Design and build transformation layers in dbt on Snowflake, including identity resolution, the semantic layer, and consumption or reporting layers.
- Build and maintain pipelines to activate data in customer engagement platforms such as Braze.
- Run discovery audits of digital products (apps, games, web) and deliver data foundation recommendations.
- Work within git-based workflows using code review, dbt tests, and existing CI/CD practices for warehouse objects.
- Define a data architecture framework with standards and principles, including modelling, metadata, security, and reference data; analyze and optimize models for performance and cost.
- Create a plan to populate new solutions with current and historical data.
- Implement data security and access controls to meet company policies and regulations.
- Document data sources, ELT/ETL processes, data dictionaries, metadata, and maintain data lineage and data flow documentation.
- Research, evaluate, and recommend new technologies while developing best practices for data management, security, and privacy.
Requirements
- Bachelor’s degree in Computer Science, Information Systems, or a related field.
- At least 5 years of experience in data engineering or a related field.
- Expert-level SQL with strong experience in ELT/ETL and cloud data warehousing, including hands-on Snowflake experience.
- Strong hands-on experience with dbt (modelling, tests, documentation, macros) and git-based workflows (branching, code review, CI/CD).
- Proven data modelling experience, including dimensional and semantic layers, and analysis techniques.
- Experience with customer data modelling and identity resolution across CRM, marketing, and product sources.
- Experience integrating with customer engagement platforms such as Braze, Salesforce Marketing Cloud, and Sailthru or similar.
- Experience planning data migrations (source audit, mapping, target structure definition, historical backfill).
- Working knowledge of Python for data tooling and automation.
- Working knowledge of at least one major cloud platform: AWS or GCP.
- Ability to troubleshoot data issues and develop effective solutions.
- Comfort producing written guidelines and recommendations for client and third-party teams.
- Understanding of data privacy and security best practices.
- Excellent communication and problem-solving skills, with fluent English.
Location & Work Setup
- APPLY is hybrid/remote-friendly.
- The preferred candidate should be based in Latin America, preferably working hours aligned to PT (Pacific Time) or ET (Eastern Timezone).
- Candidates in Santiago, Chile can work out of the Santiago office as remote/hybrid employees.
- Candidates outside Santiago, Chile will be fully remote.
Technology Stack
Snowflake, dbt, ELT, ETL, SQL, git, CI/CD, Python, AWS, GCP, Salesforce, Sailthru, Braze, Salesforce Marketing Cloud, Spark/PySpark, Docker, Kubernetes.
Nice to Have
- Snowflake (SnowPro) or dbt certification; cloud certifications welcome.
- Spark/PySpark.
- Docker and Kubernetes.
- Experience with consumer or digital-product data (apps, games, subscriptions).
Benefits
- Agentic Delivery.
- An inclusive and safe environment.
- AI & Strategic Upskilling.
- Generous vacation policy.
- Flexible work arrangements.