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Jobs/Data Engineer Role/Truelogic - Senior/Lead Data Engineer – AI-Native Aftermarket Platform
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Truelogic

Truelogic - Senior/Lead Data Engineer – AI-Native Aftermarket Platform

Remote - Panama3d ago
RemoteStaffLATAMCloud ComputingData AnalyticsData EngineerSenior Data EngineerdbtData QualitySQLpytestPythonDocumentationDatabricksGitAzureVaultClaudeSnowflakeData GovernanceMentoring

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Requirements

• Expertise in SQL and dimensional modeling methodologies, including medallion architecture, SCDs, and grain management. • Proven ability to design idempotent pipelines utilizing incremental, checkpoint, and replaceWhere strategies. • Extensive experience with production-grade Python engineering, including type hints, pytest, and ruff. • Python • pytest • Strong capability to diagnose and resolve failing Spark / PySpark jobs utilizing tools like Spark UI. • Spark • PySpark • Spark UI • Deep understanding of Delta Lake features such as MERGE, OPTIMIZE, Z-ORDER, and time travel. • Delta Lake • 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. • Databricks Asset Bundles (DAB) • Unity Catalog • Commitment to data quality via pre-write asserts, schema checks, and maintaining dbt relationship and uniqueness tests. • Strong adherence to disciplined Git workflows, conventional commits, and strict documentation practices. • Experience provisioning and utilizing Service Principals, GitHub environment secrets, and secret management tools like Azure Key Vault or Databricks secret scopes. • GitHub • Azure Key Vault • Databricks • Strong written technical communication skills for PR descriptions and runbooks, with the ability to translate pipeline work into business metrics. • Proven decision-making abilities to navigate ambiguity and balance trade-offs between cost, latency, and reliability. • Experience leading technical initiatives, establishing architectural standards, and contributing to interview rubrics is preferred. • Experience reading or modifying Azure Data Factory (ADF) pipelines and familiarity with Azure Data Lake storage is highly preferred. • Azure Data Factory (ADF) • Azure Data Lake • Familiarity with dbt observability tools, such as Elementary, is a plus. • Elementary • Awareness of PII detection and masking best practices is preferred. • Experience with multi-tenant configuration patterns to onboard new tenants with zero code changes is a strong plus. • Proficiency in reading and editing GitHub Actions workflows for Databricks deployment is preferred. • GitHub Actions • Databricks • Ability to make cost-aware compute decisions, selecting the appropriate cluster shape per workload, is a plus. • Proficiency in AI-assisted development tools like Claude Code for daily work and code review is preferred. • Claude Code • Experience writing incident post-mortems and coordinating feature handovers with Data Science teams is a plus.

Responsibilities

• Design and build robust, idempotent data pipelines from scratch utilizing a modern data stack. • Design star and snowflake schemas, writing precise, grain-aware SQL to construct scalable data marts. • Write production-grade, unit-tested Python code at the module level, adhering to strong engineering disciplines such as type hinting and testing. • Python • Build and test dbt models across staging, intermediate, and mart layers while managing overall project structure. • Author and deploy jobs using Databricks Asset Bundles (DAB) following documented architectural patterns. • Databricks Asset Bundles (DAB) • Implement rigorous data quality checks at source, intermediate, and destination layers to prevent silent drops of nulls or duplicates. • Maintain data governance through comprehensive dbt tests and strict documentation-at-merge-time discipline. • Operate securely within a multi-repository architecture, utilizing service principals and ensuring zero personal credentials in production deployments. • Run cross-repository exposure checks prior to merging schema-breaking changes. • Own data pipelines end-to-end, making key technical design decisions and mentoring mid-level engineers through substantive code reviews. • Define overarching technical direction across core data systems, including modeling standards, branching strategies, observability thresholds, and secret management policies. • Act as a technical leader to unblock the team and actively participate in hiring panels to scale the engineering organization.

Benefits

• 100% Remote Work: Enjoy the freedom to work from the location that helps you thrive. All it takes is a laptop and a reliable internet connection. • Highly Competitive USD Pay: Earn an excellent, market-leading compensation in USD, that goes beyond typical market offerings. • Paid Time Off: We value your well-being. Our paid time off policies ensure you have the chance to unwind and recharge when needed. • Work with Autonomy: Enjoy the freedom to manage your time as long as the work gets done. Focus on results, not the clock. • Work with Top American Companies: Grow your expertise working on innovative, high-impact projects with Industry-Leading U.S. Companies. • A Culture That Values You: We prioritize well-being and work-life balance, offering engagement activities and fostering dynamic teams to ensure you thrive both personally and professionally. • Diverse, Global Network: Connect with over 600 professionals in 25+ countries, expand your network, and collaborate with a multicultural team from Latin America. • Team Up with Skilled Professionals: Join forces with senior talent. All of our team members are seasoned experts, ensuring you're working with the best in your field.

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