Senior Data Engineer: Snowflake & dbt - Remote

Apply Digital

Santiago

Hybrid

CLP 89,197,000 - 138,751,000

Full time

9 days ago

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Job summary

Apply Digital in a hybrid/remote-friendly role seeks a data engineer to translate business requirements into technical specifications, design data pipelines, and implement data security and governance.

You will work with Snowflake, dbt, Python and cloud platforms, perform data migrations, modelling and identity resolution, and collaborate with global clients in Latin America to deliver scalable data solutions.

Qualifications

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.

Responsibilities

Define data requirements and technology stack for projects.
Audit source systems and define migration guidelines for execution.
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 and produce data foundation recommendations.
Define data architecture framework, standards and principles, including modelling, metadata, security and reference data.
Create a plan of activities to populate new solutions with all current and historical data.
Implement data security and access controls to ensure compliance.
Document data sources, ELT/ETL processes, data dictionaries and metadata to facilitate data discovery.