Sr. Data Engineer

Apply DigitalRemote - Santiago / Latin America / Mexico City3w ago

Remote Senior NA Artificial Intelligence Logistics Cloud Computing Data Engineer Digital Artist Digital Designer SQL Reporting Python GCP Airflow

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Requirements

Strong proficiency in English (written and verbal communication) is required.
Experience working with remote teams, ensuring smooth collaboration across time zones.
5+ years of experience in data engineering, with expertise in building scalable data pipelines and cloud-native data architectures.
Strong proficiency in SQL for data modeling, transformation, and performance optimization.
Expertise in Python for data processing, automation, and pipeline development.
Experience with cloud data platforms, particularly Google Cloud Platform (GCP).
Hands-on experience with Google BigQuery, Cloud Storage, and Pub/Sub.
Strong knowledge of ETL/ELT frameworks such as DBT, Dataflow, or Apache Beam.
Familiarity with workflow orchestration tools like Dagster, Apache Airflow or Google Cloud Workflows.
Understanding of data privacy, security, and compliance best practices.
Strong problem-solving skills, with the ability to debug and optimize complex data workflows.
Excellent communication and collaboration skills.
Experience with real-time data streaming solutions (e.g., Kafka, Pub/Sub, or Kinesis).
Familiarity with machine learning workflows and MLOps best practices.
Experience with designing and implementing data solutions with Snowflake.
Proficiency with the Databricks platform.
Experience with BI and data visualization tools (e.g., Looker, Tableau, or Google Data Studio).
Knowledge of Terraform for Infrastructure as Code (IaC) in data environments.
Familiarity with data integrations involving Contentful, Algolia, Segment, and Talon.One.
LIFE AT APPLY DIGITAL
At Apply Digital, people are at the core of everything we do. We value your time, safety, and health, and strive to build a work community that can help you thrive and grow. Here are a few benefits we offer to support you:
Great projects: Broaden your skills on a range of engaging projects with international brands that have a global impact.
An inclusive and safe environment: We’re truly committed to building a culture where you are celebrated and everyone feels welcome and safe.
Learning opportunities: We offer generous training budgets, including partner tech certifications, custom learning plans, workshops, mentorship, and peer support.
Generous vacation policy: Work-life balance is key to our team’s success, so we offer ample time away from work to promote overall well-being.
Customizable benefits: Tailor your extended health and dental plan to your needs, priorities, and preferences.
Flexible work arrangements: We work in a variety of ways, from remote, to in-office, to a blend of both.
For more information, visit the Diversity, Equity, and Inclusion (DEI) section of our website. If you have accommodation needs at this stage of the recruitment process, please inform us as soon as possible by emailing us at [email protected].

Responsibilities

Design, build, and maintain scalable data pipelines and architectures to support analytical and operational workloads.
Develop and optimize ETL/ELT pipelines, ensuring efficient data extraction, transformation, and loading from various sources.
Work closely with backend and platform engineers to integrate data pipelines into cloud-native applications.
Manage and optimize cloud data warehouses, primarily BigQuery, ensuring performance, scalability, and cost efficiency.
Implement data governance, security, and privacy best practices, ensuring compliance with company policies and regulations.
Collaborate with analytics teams to define data models and enable self-service reporting and BI capabilities.
Develop and maintain data documentation, including data dictionaries, lineage tracking, and metadata management.
Monitor, troubleshoot, and optimize data pipelines, ensuring high availability and reliability.
Stay up to date with emerging data engineering technologies and best practices, continuously improving our data infrastructure.