Senior/Lead Data Engineer – AI-Native Aftermarket Platform

This is a fully remote position, open to applicants in Argentina.

📋 Description

• Create and develop resilient, idempotent data pipelines from the ground up using a contemporary data stack.

• Design star and snowflake schemas, crafting precise, grain-aware SQL to build scalable data marts.

• Produce production-grade, unit-tested Python code at the module level, adhering to robust engineering principles such as type hinting and testing.

• Construct and validate dbt models across staging, intermediate, and mart layers while overseeing the overall project structure.

• Author and deploy jobs utilizing Databricks Asset Bundles (DAB) in accordance with documented architectural patterns.

• Enforce stringent data quality checks at source, intermediate, and destination layers to prevent unnoticed nulls or duplicates.

• Uphold data governance through thorough dbt tests and a strict documentation-at-merge-time approach.

• Function securely within a multi-repository architecture, employing service principals and ensuring no personal credentials are present in production deployments.

• Execute cross-repository exposure checks prior to merging schema-altering changes.

• Own data pipelines from start to finish, making crucial technical design decisions and mentoring mid-level engineers through comprehensive code reviews.

• Establish the overarching technical direction across core data systems, including modeling standards, branching strategies, observability thresholds, and secret management policies.

• Serve as a technical leader to facilitate team progress and actively engage in hiring panels to expand the engineering organization.

⛳️ Requirements

• Proficiency in SQL and dimensional modeling techniques, including medallion architecture, SCDs, and grain management.

• Demonstrated ability to design idempotent pipelines using incremental, checkpoint, and replaceWhere strategies.

• Extensive background in production-grade Python engineering, featuring type hints, pytest, and ruff.

• Strong ability to troubleshoot and resolve failing Spark / PySpark jobs with tools like Spark UI.

• Comprehensive understanding of Delta Lake functionalities such as MERGE, OPTIMIZE, Z-ORDER, and time travel.

• Practical expertise in dbt, encompassing models, tests, and exposures.

• Experience in authoring and deploying jobs with Databricks Asset Bundles (DAB) while functioning within a Unity Catalog environment.

• Commitment to data quality through pre-write asserts, schema checks, and maintaining dbt relationship and uniqueness tests.

• Strong compliance with disciplined Git workflows, conventional commits, and rigorous documentation standards.

• Familiarity with provisioning and utilizing Service Principals, GitHub environment secrets, and secret management solutions like Azure Key Vault or Databricks secret scopes.

• Excellent written technical communication skills for PR descriptions and runbooks, with the capability to translate pipeline work into business metrics.

• Proven ability to make decisions amid uncertainty and balance trade-offs between cost, latency, and reliability.

• Preferred experience in leading technical initiatives, establishing architectural standards, and contributing to interview rubrics.

• Highly preferred experience in reading or modifying Azure Data Factory (ADF) pipelines and familiarity with Azure Data Lake storage.

• Familiarity with dbt observability tools, such as Elementary, is a bonus.

• Preferred awareness of PII detection and masking best practices.

• Strongly preferred experience with multi-tenant configuration patterns to onboard new tenants without code changes.

• Preferred proficiency in reading and editing GitHub Actions workflows for Databricks deployment.

• Ability to make cost-aware compute choices, selecting the right cluster shape for each workload, is a plus.

• Preferred proficiency in AI-assisted development tools like Claude Code for daily tasks and code review.

• Bonus experience in writing incident post-mortems and coordinating feature handovers with Data Science teams.

🏝️ Benefits

• 100% Remote Work: Enjoy the flexibility to work from wherever you feel most productive. All you need is a laptop and a stable internet connection.

• Highly Competitive USD Pay: Receive an outstanding, market-leading salary in USD that surpasses standard market offerings.

• Paid Time Off: We prioritize your well-being. Our paid time off policies ensure you have the opportunity to relax and recharge when necessary.

• Work with Autonomy: Experience the freedom to manage your schedule as long as the work is completed. Focus on outcomes, not the clock.

• Collaborate with Top American Companies: Enhance your skills by working on innovative, high-impact projects with industry-leading U.S. companies.