Senior Data Engineer

APPLY’s Data team is hiring a Senior Data Engineer to design and take ownership of modern data foundations. The role focuses on building ELT and modelling layers on Snowflake with dbt, enabling downstream activation into customer engagement platforms, and partnering with stakeholders and clients to define requirements and delivery plans.

Responsibilities

• Collaborate with internal disciplines, 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 establish migration guidelines covering what to migrate, target structure, and execution order for internal or third-party teams.
• Translate business needs into technical specifications, including data streams, integrations, transformations, databases, and data warehouses.
• Design and build transformation layers in dbt on Snowflake, including identity resolution, semantic layer work, and consumption or reporting layers.
• Build and maintain pipelines that activate data within customer engagement platforms such as Braze.
• Conduct discovery audits of digital products (apps, games, web) and produce data foundation recommendations.
• Work in git-based workflows with code review, dbt tests, and existing CI/CD processes for warehouse objects.
• Define a data architecture framework, standards, and principles, including modelling, metadata, security, and reference data; analyze and optimize existing models for performance and cost.
• Create plans to populate new solutions with both current and historical data.
• Implement data security and access controls to support compliance with company policies and regulations.
• Document data sources, ELT/ETL processes, data dictionaries, and metadata to enable data discovery; maintain data lineage and data flow documentation.
• Research, evaluate, and recommend new technologies, and develop 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 related fields.
• Expert-level SQL with hands-on experience in ELT/ETL and cloud data warehousing, including Snowflake.
• Strong hands-on experience with dbt (modelling, tests, documentation, macros) and git-based workflows (branching, code review, CI/CD).
• Proven ability in data modelling (dimensional and semantic layers) and analytical 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, and Sailthru (or similar).
• Experience planning data migrations between platforms, including source audit, mapping, target structure definition, and historical backfill.
• Working knowledge of Python for data tooling and automation.
• Working knowledge of at least one major cloud platform: AWS or GCP and relevant data services.
• 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.
• Fluent English.

Technologies

Snowflake, dbt, ELT, ETL, SQL, git, CI/CD, Python, AWS, GCP, Salesforce, Sailthru, Braze, Salesforce Marketing Cloud, Spark/PySpark, Docker, Kubernetes

Benefits

• Agentic Delivery.
• An inclusive and safe environment.
• AI & Strategic Upskilling.
• Generous vacation policy.
• Flexible work arrangements.

Location

• APPLY is hybrid/remote-friendly.
• The preferred candidate should be based in Latin America, ideally working hours aligned to PT (Pacific Time) or ET (Eastern Time).
• Candidates located in Santiago, Chile can work out of the Santiago office as remote/hybrid employees.
• Candidates located outside Santiago, Chile will be fully remote employees.
• Location is listed as Arkansas (hybrid).

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).