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Data Engineer (Databricks)

3 weeks, 4 days ago
Peru
Full-time
Senior
Data Engineer
Software Development
Apache Spark AWS Azure CI/CD Databricks dbt GCP Git GitHub Go Java Kafka MLflow MLOps Python Scala SQL
Apply Now
Livefront

Livefront

Since 2001, Livefront has helped companies grow by designing, building, and scaling digital products people love. Let's create something remarkable, together.

Internet Software & Services
11-50
View All Jobs 3

Description

  • Design and build production data pipelines using Lakeflow Declarative Pipelines, Autoloader, Structured Streaming, and Declarative Automation Bundles.
  • Architect and implement Lakehouse solutions on Databricks, including medallion architecture, Delta Lake, and Unity Catalog.
  • Build and maintain Databricks transformation layers using DLT pipelines, PySpark notebooks, and dbt.
  • Design and maintain data and AI foundations such as Unity Catalog, Feature Store, MLflow, and Model Serving.
  • Collaborate with product and backend engineers on data models, APIs, and application data contracts.
  • Consult with clients to assess data challenges, develop data strategies, and implement sustainable solutions.
  • Lead or support data architecture discussions depending on project needs.
  • Work within multi-cloud environments, primarily AWS and Azure, and align Databricks recommendations to client architecture and goals.
  • Champion data governance, including access control, lineage, data quality policies, and compliance.
  • Design data-to-application architectures, including Lakebase-backed services and Databricks Apps, for governed AI workflows and user-facing experiences.
  • Contribute to Livefront’s Databricks practice through accelerators, internal enablement, certifications, and partner go-to-market materials.

Requirements

  • 3-5 years of data engineering experience with at least 2 years in production Databricks environments, preferably in consulting or client delivery.
  • Strong working knowledge of AWS and Azure cloud services relevant to Databricks deployments, including storage, networking, IAM, and compute.
  • Production-grade Databricks expertise with Lakeflow Declarative Pipelines, Autoloader, Structured Streaming, Lakeflow Jobs, and Unity Catalog.
  • Experience designing Lakehouse architectures, including medallion patterns, Delta Lake table design, partitioning, Z-ordering, and query optimization.
  • Hands-on experience with data pipeline testing, observability, and CI/CD, including unit testing, data quality frameworks, Git, and Declarative Automation Bundles.
  • Strong proficiency in SQL and Python for clean, performant, and maintainable code.
  • Understanding of data modeling, schema design, and query optimization.
  • Excellent communication skills for explaining complex data concepts to technical and non-technical stakeholders.
  • Strong problem-solving ability for ambiguous requirements and pragmatic solutions.
  • GCP familiarity is a plus.
  • Obvious comfort with critique and peer review in an iterative development process.
  • Experience with real-time streaming technologies such as Kafka or Kinesis is a bonus.
  • Hands-on experience with MLOps or LLMOps on Databricks is a bonus, including MLflow, Model Serving, or Vector Search.
  • Experience with Java, Go, or Scala is a bonus.
  • A Databricks certification or active pursuit of one, such as Data Engineer Associate, Data Engineer Professional, or Apache Spark Developer, is a bonus.

Benefits

  • Remote work opportunity in Peru.
  • The chance to work with household-name brands and high-impact products that reach millions of people.
  • A collaborative, respectful work environment with mutual trust and egoless teamwork.
  • A team culture that values quality, craftsmanship, and continuous improvement.
  • Opportunities to help build a Databricks practice from the ground up and shape its go-to-market strategy.
  • A fast-moving hiring process with a take-home exercise that can be completed in up to a week.
  • Commitment to merit-based, inclusive hiring with every application reviewed by a human.

Interested in this position?

Apply directly on the company website

Apply Now

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