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

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

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