Senior/Lead Data Engineer – AI-Native Aftermarket Platform

Remote from
LATAM flag
LATAM
Annual salary
Undisclosed
Salary information is not provided for this position. Check our Salary Directory to estimate the average compensation for similar roles.
Employment type
Full Time,
Job posted
Apply before
12 Jul 2026
Experience level
Senior
Views / Applies
14 / 2

About Truelogic

Accelerate Your Digital Transformation

Actively Hiring
Verified job posting
This job post has been manually reviewed for authenticity and compliance.

AI Summary

Truelogic is seeking a Senior/Lead Data Engineer for an AI-native aftermarket platform client. The role involves designing robust data pipelines using a modern data stack including dbt, Databricks, and Python. Responsibilities include data modeling, implementing data quality checks, mentoring junior engineers, and setting technical direction. The ideal candidate has deep expertise in SQL, Python, dimensional modeling, and Delta Lake, with leadership experience. This is a remote position with a focus on high-impact machine learning projects.

Role DNA

Job Complexity
Easy Hard
Pace & Pressure
Relaxed Fast-paced
Autonomy Level
Guided Full Ownership
Communication Load
Independent Highly Collaborative
AI Insight The role requires advanced technical skills in data engineering, including production-grade Python, dbt, Spark, and Delta Lake, as well as leadership and mentoring capabilities, making it highly challenging.

Salary Analysis

Median Highly Competitive
$155,000
US Market
$120k – 190k
0 $209k
AI Insight The salary for this role is estimated based on market data for Senior/Lead Data Engineers. The compensation is competitive, aligning with the expertise required and the value delivered to the AI-native platform. Candidates can expect a strong total package including equity and benefits.

Key Skills

Data Engineering Python SQL dbt Databricks Apache Spark Data Modeling Data Pipelines Delta Lake Machine Learning

I am writing to express my interest in the Senior/Lead Data Engineer position at your AI-native aftermarket platform. With extensive experience in designing scalable data pipelines using modern tools like dbt, Databricks, and Python, I am excited to contribute to your mission of optimizing the global equipment aftermarket.

In my previous role, I led the architecture of end-to-end data solutions, ensuring data quality and governance through rigorous testing and documentation. My proficiency in dimensional modeling, Delta Lake, and Spark has enabled me to deliver high-performance analytics and machine learning models.

I thrive in collaborative environments and have mentored team members, conducted code reviews, and defined technical strategies. I look forward to bringing my technical leadership and passion for data engineering to your innovative team.

Thank you for considering my application. I am eager to discuss how my skills align with your needs.

Describe your experience designing data pipelines using dbt and how you ensure data quality.
I have built multiple dbt models across staging, intermediate, and mart layers. I implement rigorous tests like unique, not null, and referential integrity, and use custom tests for business logic. I also set up data quality checks at source and destination using tools like Great Expectations.
Explain how you handle incremental loading in Databricks using Delta Lake.
I use Delta Lake's MERGE operation for upserts, along with replaceWhere for partition overwrites. I also leverage OPTIMIZE and Z-ORDER for performance. For streaming, I use structured streaming with checkpointing.
Walk me through a complex data pipeline you built from scratch, including the technology stack and architecture.
I built a pipeline for a customer 360 view using Kafka for ingestion, Spark for processing, and dbt for transformations. Data was stored in Delta Lake on Databricks, with medallion architecture (bronze, silver, gold). I designed star schema data marts for analytics.
How do you mentor junior engineers and handle code reviews to maintain high standards?
I conduct weekly pair programming sessions and provide constructive feedback on code reviews focusing on engineering principles like type hinting, testing, and documentation. I also set up coding standards and encourage knowledge sharing through tech talks.
What strategies do you use to ensure data governance and security in a multi-repository environment?
I enforce strict documentation-at-merge-time, use service principals for deployments, and implement exposure checks before merging schema changes. I also set up secret management using Databricks secrets and ensure zero personal credentials in production.

About Truelogic

At Truelogic we are a leading provider of nearshore staff augmentation services headquartered in New York. For over two decades, we’ve been delivering top-tier technology solutions to companies of all sizes, from innovative startups to industry leaders, helping them achieve their digital transformation goals.

Our team of 600+ highly skilled tech professionals, based in Latin America, drives digital disruption by partnering with U.S. companies on their most impactful projects. Whether collaborating with Fortune 500 giants or scaling startups, we deliver results that make a difference.

By applying for this position, you’re taking the first step in joining a dynamic team that values your expertise and aspirations. We aim to align your skills with opportunities that foster exceptional career growth and success while contributing to transformative projects that shape the future.

Our Client

Well-funded, AI-native software company building a connected platform that maximizes the global equipment aftermarket for OEMs, dealers, and fleets. Backed by a premier AI incubator and a leading heavy-duty manufacturing enterprise, they deliver machine learning-driven insights to optimize inventory, service, and sales.

Job Summary

We are seeking a highly skilled and motivated Data Engineer to build, maintain, and scale the critical data pipelines powering an innovative AI-native platform. In this role, you will design robust architectures, ensure pristine data quality, and implement modern data stack solutions to drive high-impact machine learning models and analytics. The ideal candidate is an expert in data modeling and Python engineering who thrives in a collaborative environment, demonstrating the technical depth to own complex pipelines end-to-end and the leadership capability to mentor peers, set architectural standards, and drive the team’s overarching data strategy.

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.

  • 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.

  • 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.

Qualifications and Job 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.

  • Strong capability to diagnose and resolve failing Spark / PySpark jobs utilizing tools like Spark UI.

  • Deep understanding of Delta Lake features such as MERGE, OPTIMIZE, Z-ORDER, and 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 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.

  • 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.

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

  • 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.

  • 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.

  • Experience writing incident post-mortems and coordinating feature handovers with Data Science teams is a plus.

What We Offer

  • 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.

Why You’ll Like Working Here

  • 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.

Apply now!

Apply now >

This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

How to apply

Did you apply? Let us know, and we’ll help you track your application.

See a few more

Similar Data Science & Analytics remote jobs

Job Search Safety Tips

Here are some tips to help you search and apply for jobs safely:
Watch out for suspicious jobs Don't apply for jobs that offer high pay for little work or offer to hire you without an interview. Read more ›
Check the employer's profile Make sure you're applying for a trustworthy job by visiting the employer's profile and learning more about them. Read more ›
Protect your information Don't share personal details like your bank account or government-issued ID on suspicious websites or messengers. Read more ›
Report jobs that feel unsafe If you see a job that seems misleading, inappropriate or discriminatory, report it for going against our policies and we'll review it.

Share this job

Jobicy+ Subscription

Jobicy

614 professionals pay to access exclusive and experimental features on Jobicy

Free

USD $0/month

For people just getting started

  • • Unlimited applies and searches
  • • Access on web and mobile apps
  • • Weekly job alerts and digest
  • • Access to additional tools like Bookmarks, Applications, and more

Plus

USD $8/month

Everything in Free, and:

  • • Ad-free experience
  • • Daily job alerts and digest
  • • Personal career consultant
  • • AI-powered job advice
Go to account ›