Sr. Data Architect

Overview

A senior Data Engineer to design and maintain scalable data pipelines on AWS, ensuring performance, quality, and security. You will collaborate with data scientists and analysts to integrate data from multiple sources and support AI/ML initiatives.

Key Responsibilities

• Build and optimize ETL pipelines with AWS Glue.
• Work with AWS S3, Glue, and SageMaker for data and AI workflows.
• Develop solutions in Python and SQL.
• Integrate data from Salesforce and APIs.
• Ensure data governance, documentation, and best practices.
• AWS (S3, Glue, SageMaker)
• Python, SQL

Requirements

• Proven experience in data engineering with AWS.
• Experience with ETL, data modeling, and pipeline optimization.
• Advanced English (international collaboration).

What You Will Do

• Designing performant data pipelines for the ingestion and transformation of complex datasets into usable data products.
• Building scalable infrastructure to support hourly, daily, and weekly update cycles.
• Implementing automated QA checks and monitoring systems to catch data anomalies before they reach clients.
• Re-architecting system components to improve performance or reduce costs.
• Supporting team members through code reviews and collaborative development.
• Building enterprise-grade batch and real-time data processing pipelines on AWS, with a focus on serverless architectures.
• Designing and implementing automated ELT processes to integrate disparate datasets.
• Collaborating across multiple teams to ingest, extract, and process data using Python, R, Zsh, SQL, REST, and GraphQL APIs.
• Transforming clickstream and CRM data into meaningful metrics and segments for visualization.
• Creating automated acceptance, QA, and reliability checks to ensure business logic and data integrity.
• Designing appropriately normalized schemas and making informed decisions between SQL and NoSQL solutions.
• Optimizing infrastructure and schema design for performance, scalability, and cost efficiency.
• Defining and maintaining CI/CD and deployment pipelines for data infrastructure.
• Containerizing and deploying solutions using Docker and AWS ECS.
• Proactively identifying and resolving data discrepancies, and implementing safeguards to prevent recurrence.
• Contributing to documentation, onboarding materials, and cross-team enablement efforts.

What You Will Bring

• Bachelor's degree in Computer Science, Software Engineering, or a related field; additional training in statistics, mathematics, or machine learning is a strong plus.
• 5+ years of experience building scalable and reliable data pipelines and data products in a cloud environment (AWS preferred).
• Deep understanding of ELT processes and data modeling best practices.
• Strong programming skills in Python or a similar scripting language.
• Advanced SQL skills, with intermediate to advanced experience in relational database design.
• Familiarity with joining and analyzing large behavioral datasets, such as Adobe and GA4 clickstream data.
• Excellent problem-solving abilities and strong attention to data accuracy and detail.
• Proven ability to manage and prioritize multiple initiatives with minimal supervision.

Nice to Have

• Experience working with data transformation tools such as Data Build Tool or similar technologies.
• Familiarity with Docker containerization and orchestration.
• Experience in API design or integration for data pipelines.
• Development experience in a Linux or Mac environment.
• Exposure to data QA frameworks or observability tools (e.g., Great Expectations, Monte Carlo, etc.).

What We Offer

• 100% Remote Work
• WFH allowance: Monthly payment as financial support for remote working.
• Career Growth: Career development program with 360º feedback.
• Training: Time allocated for tech training, English classes, books, conferences, and events.
• Mentoring Program: You can mentor or receive mentorship, or both.
• Zartis Wellbeing Hub (Kara Connect): Access to sessions with health and wellness professionals.
• Multicultural working environment: Tech events, webinars, and team-building activities.

About The Role

We are seeking experienced Data Engineers to develop and deliver robust, cost-efficient data products that power analytics, reporting and decision-making across two distinct brands.

What You'll Do

• Build highly consumable and cost-efficient data products by synthesizing data from diverse source systems.
• Ingest raw data using Fivetran and Python, staging and enriching it in BigQuery to provide consistent, trusted dimensions and metrics for downstream workflows.
• Design, maintain, and improve workflows that ensure reliable and consistent data creation, proactively addressing data quality issues and optimizing for performance and cost.
• Develop LookML Views and Models to democratize access to data products and enable self-service analytics in Looker.
• Deliver ad hoc SQL reports and support business users with timely insights.
• (Secondary) Implement simple machine learning features into data products using tools like BQML.
• Build and maintain Looker dashboards and reports to surface key metrics and trends.

What We're Looking For

• Proven experience building and managing data products in modern cloud environments (GCP preferred).
• Strong proficiency in Python for data ingestion and workflow development.
• Hands-on expertise with BigQuery, dbt, Airflow and Looker.
• Solid understanding of data modeling, pipeline design and data quality best practices.
• Excellent communication skills and a track record of effective collaboration across technical and non-technical teams.

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