Senior/Lead Data Engineer – AI-Native Aftermarket Platform

Senior/Lead Data Engineer – AI-Native Aftermarket Platform

Company: Truelogic Location: LATAM (Remote) Industry: Technology

About the Role

Truelogic is seeking a highly skilled and motivated Senior/Lead Data Engineer to join a dynamic team. You will be instrumental in building, maintaining, and scaling critical data pipelines for an innovative AI-native platform focused on the global equipment aftermarket. This role involves designing robust architectures, ensuring exceptional data quality, and implementing modern data stack solutions to power high-impact machine learning models and analytics. The ideal candidate is an expert in data modeling and Python engineering, capable of owning complex pipelines end-to-end, mentoring peers, setting architectural standards, and driving the team's data strategy.

Key Responsibilities

• Design and build robust, idempotent data pipelines from scratch using a modern data stack.
• Develop star and snowflake schemas, writing precise SQL to construct scalable data marts.
• Write production-grade, unit-tested Python code with strong engineering disciplines (type hinting, testing).
• Build and test dbt models across staging, intermediate, and mart layers, managing overall project structure.
• Author and deploy jobs using Databricks Asset Bundles (DAB), following documented architectural patterns.
• Implement rigorous data quality checks at all layers to prevent data integrity issues.
• Maintain data governance through comprehensive dbt tests and strict documentation practices.
• Operate securely within a multi-repository architecture, utilizing service principals and ensuring no personal credentials in production.
• Perform cross-repository exposure checks before merging schema-breaking changes.
• Own data pipelines end-to-end, making key technical design decisions and mentoring mid-level engineers through code reviews.
• Define technical direction for core data systems, including modeling standards, branching strategies, and observability.
• Act as a technical leader to unblock the team and participate in hiring to scale the engineering organization.

Requirements

• Expertise in SQL and dimensional modeling methodologies (medallion architecture, SCDs, grain management).
• Proven ability to design idempotent pipelines using incremental, checkpoint, and replaceWhere strategies.
• Extensive experience with production-grade Python engineering, including type hints, pytest, and ruff.
• Strong capability to diagnose and resolve failing Spark/PySpark jobs using tools like Spark UI.
• Deep understanding of Delta Lake features (MERGE, OPTIMIZE, Z-ORDER, time travel).
• Hands-on expertise with dbt, including models, tests, and exposures.
• Experience authoring and deploying jobs using Databricks Asset Bundles (DAB) and operating within a Unity Catalog environment.
• Commitment to data quality via pre-write asserts, schema checks, and dbt tests.
• Strong adherence to disciplined Git workflows, conventional commits, and documentation practices.
• Experience provisioning and utilizing Service Principals, GitHub environment secrets, and secret management tools (e.g., Azure Key Vault, Databricks secret scopes).
• Strong written technical communication skills for PR descriptions and runbooks.
• Proven decision-making abilities to navigate ambiguity and balance trade-offs (cost, latency, reliability).
• Experience leading technical initiatives and establishing architectural standards is preferred.
• Experience with Azure Data Factory (ADF) pipelines and Azure Data Lake storage is highly preferred.
• Familiarity with dbt observability tools (e.g., Elementary) is a plus.
• Awareness of PII detection and masking best practices is preferred.
• Experience with multi-tenant configuration patterns is a strong plus.
• Proficiency in reading and editing GitHub Actions workflows for Databricks deployment is preferred.
• Ability to make cost-aware compute decisions is a plus.
• Proficiency in AI-assisted development tools (e.g., Claude Code) is preferred.
• Experience writing incident post-mortems and coordinating handovers with Data Science teams is a plus.

What We Offer

• 100% Remote Work: Work from anywhere with a reliable internet connection.
• Highly Competitive USD Pay: Earn market-leading compensation in USD.
• Paid Time Off: Comprehensive policies to ensure you can rest and recharge.
• Work with Autonomy: Focus on results and manage your time effectively.
• Work with Top American Companies: Contribute to innovative, high-impact projects with industry-leading U.S. companies.
• A Culture That Values You: Prioritizing well-being, work-life balance, and professional growth.
• Diverse, Global Network: Connect with over 600 professionals in 25+ countries.
• Team Up with Skilled Professionals: Collaborate with seasoned experts in your