🕒 2 days ago
Scale the data platform by building reliable pipelines, improving data models and quality, and enabling lower-latency analytics while shaping engineering practices as the team grows.
Senior Data Engineer
🕒 2 days ago
SQLSnowflakeDbtELT/ETL
📜 Description
- Define project data requirements and technology stacks with clients, vendors, and internal teams.
- Audit CRM and marketing sources and create migration guidelines, mappings, and historical backfill plans.
- Translate business needs into technical specifications for data streams, integrations, transformations, and warehouses.
- Build dbt transformation layers in Snowflake, including identity resolution, semantic, and consumption layers.
- Develop and maintain data activation pipelines for customer engagement platforms such as Braze.
- Set data architecture standards, optimize models, implement access controls, and document data lineage and processes.
🛠️ Requirements
- A 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 and strong experience in ELT/ETL and cloud data warehousing, with hands-on Snowflake experience.
- Strong hands-on experience with dbt (modelling, tests, documentation, macros) and git-based workflows (branching, code review, CI/CD).
- Proven experience in data modelling (dimensional and semantic layers) and analysis techniques.
- Experience with customer data modelling and identity resolution across CRM, marketing and product sources.
- Experience integrating data with customer engagement platforms (Braze, Salesforce Marketing Cloud, Sailthru or similar).
- Experience planning data migrations between platforms: 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 its data services.
✨ Benefits
- Generous training budgets and mentorship, including Agentic AI upskilling.
- Ample vacation time.
- Flexible work arrangements.
- Inclusive and safe work environment.
Full job description
ABOUT APPLY
APPLY is the Agentic Customer Experience (ACx) partner for the world's most ambitious consumer and entertainment brands. We bring together deep domain expertise across Retail, CPG, Sports, and Media with AI-native delivery capability, designing and delivering agentic solutions that turn CX vision into commercial reality. We are the partner of choice for brands like Arc'teryx, NFL, Lululemon, and Kraft Heinz. For more information, visit applydigital.com.
LOCATION: APPLY is hybrid/remote-friendly. The preferred candidate should be based in Latin America, preferably working in hours that align to PT (Pacific Timezone) or ET (Eastern Timezone). Candidates located in Santiago, Chile are able to work out of our Santiago office as remote/hybrid employees. Candidates located outside of Santiago, Chile will be fully remote employees.
THE ROLE:
APPLY is seeking a Senior Data Engineer to join our Data team. You will build and own data foundations on modern cloud data warehouses such as Snowflake using dbt-based ELT: from source audits and migration guidelines, through modelling (identity resolution, semantic and consumption layers), to activation pipelines into customer engagement platforms such as Braze. You will work closely with cross-functional teams, clients and third-party vendors to define data requirements, translate business needs into technical specifications, and produce clear, actionable recommendations.
The successful candidate will have a strong background in data engineering on the modern data stack and excellent communication skills to interact with stakeholders and clients. If you have a passion for technology, thrive in a dynamic environment, and possess strong client-facing communication skills, we want to hear from you.
RESPONSIBILITIES:
Work with internal disciplines, vendors, clients and stakeholders to define data requirements and the technology stack for projects.
Audit source systems (CRM and marketing platforms such as Salesforce and Sailthru) and define migration guidelines: what to migrate, in what structure and in what order, for execution by internal or third-party teams.
Translate business requirements 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 and consumption/reporting layers.
Build and maintain pipelines that activate data in customer engagement platforms (e.g., Braze).
Run 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 the data architecture framework, standards and principles, including modelling, metadata, security and reference data; analyze and optimize existing architectures and models for performance and cost.
Create a plan of activities required to populate new solutions with all current and historical data.
Implement data security and access controls to ensure compliance with company policies and regulation.
Document data sources, ELT/ETL processes, data dictionaries and metadata to facilitate 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:
A 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 and strong experience in ELT/ETL and cloud data warehousing, with hands-on Snowflake experience.
Strong hands-on experience with dbt (modelling, tests, documentation, macros) and git-based workflows (branching, code review, CI/CD).
Proven experience in data modelling (dimensional and semantic layers) and analysis techniques.
Experience with customer data modelling and identity resolution across CRM, marketing and product sources.
Experience integrating data with customer engagement platforms (Braze, Salesforce Marketing Cloud, Sailthru or similar).
Experience planning data migrations between platforms: 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 its data services.
Demonstrated ability to troubleshoot data issues and develop effective solutions.
Comfortable 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.
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).
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