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Mutt Data

Delivers ML solutions for business outcomes

Data Engineer Lead - Databricks, Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeRemote in Argentina

About the Job

Requirements

  • Experience in data engineering, including building and optimizing data pipelines.
  • Experience working with Databricks, Python, and Spark to build batch and streaming solutions.
  • Advanced English proficiency.
  • Familiarity with a business intelligence visualization tool such as Looker or Tableau.

Responsibilities

  • Lead end-to-end data migration initiatives, ensuring a smooth, secure, and business-aligned transition.
  • Define and communicate data architecture decisions, evaluating impacts, risks, and performance considerations across cloud data platforms such as Amazon Web Services Redshift and Databricks.
  • Coordinate the discovery and documentation of dependencies, schema inventories, data flows, and critical processes involved in migration efforts.
  • Own migration and cutover planning, ensuring all activities, validations, and contingency measures are properly defined and executed.
  • Serve as the primary liaison between engineering, analytics, product, and business stakeholders, facilitating clear communication and alignment throughout the project lifecycle.
  • Translate technical changes in data pipelines, data warehouses, and platform architecture into clear business impact assessments.
  • Define and document assumptions, requirements, and acceptance criteria to ensure successful migration outcomes.
  • Oversee data validation processes to guarantee the accuracy, consistency, and integrity of migrated datasets against source-of-truth systems.
  • Proactively identify, assess, and mitigate migration-related risks, escalating blockers and dependencies when necessary to maintain project timelines and quality standards.
  • Drive problem-solving and decision-making in fast-paced, ambiguous environments, helping cross-functional teams stay focused on priorities and deliverables.
  • Create, maintain, and improve project documentation, including migration runbooks, testing strategies, rollback plans, and operational procedures.
  • Provide regular project status updates to technical and executive stakeholders, ensuring transparency around progress, risks, and next steps.
  • Promote data governance, quality, and operational best practices throughout the migration lifecycle.
  • Align engineers, analysts, and product stakeholders around priorities, timelines, and delivery expectations to ensure successful project execution.

About the Company

Mutt Data

Delivers ML solutions for business outcomes

Mutt Data helps startups and large enterprises build and implement machine learning solutions that deliver real business results. They work across finance, insurance, advertising, telecoms, on-demand services, and e-commerce to help clients get ahead using the latest methods and best practices. How it works: They provide end-to-end ML services, starting with understanding business goals, data assessment, data engineering, model development, deployment, and ongoing monitoring and optimization. They tailor tools and techniques to each industry to put models into production and track their impact. Differences: They serve both startups and big companies and offer a complete workflow from idea to production, across many industries, with a focus on practical business outcomes rather than research-only efforts. Goal: Help customers gain a competitive edge by turning data into deployable ML solutions that improve efficiency, revenue, and user experience.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
Capital, Argentina
Founded
2017

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