Data Engineering Project Manager - Databricks

Muttdata
Argentina
Remote

Who this role is best for

Aimed at mid-level data engineering project managers who orchestrate cloud data engagements end-to-end in a remote-first startup environment.

Best fit for

  • Candidates with 7-10+ years in IT delivery who can manage cloud data engagements from planning to execution.
    β€” β€œ7-10+ years of IT experience managing delivery and interfacing with key project stakeholders”
  • Professionals skilled in Agile project management and modern PM tools who lead cross-functional technical teams.
    β€” β€œExperience implementing and managing Agile engineering project best practices”
  • Individuals with consulting backgrounds who can juggle multiple concurrent client engagements effectively.
    β€” β€œBackground in consulting environments or managing multiple concurrent clients”
  • Leaders who have hands-on familiarity with Databricks, Spark, and major cloud platforms.
    β€” β€œHands-on experience with modern cloud data stacks (e.g., Databricks, Spark, Python, AWS, Azure, GCP)”

Things to consider

  • The role requires strong English proficiency for stakeholder communication and project reporting.
    β€” β€œStrong written and spoken English”
  • Candidates must be prepared to work under pressure while ensuring projects stay on budget and scope.
    β€” β€œcapacity to work under pressure are key to success in this role”
  • Experience in regulated industries like financial services is treated as a secondary advantage.
    β€” β€œExperience working with financial services or other regulated industry clients”

How to stand out

  • Highlight specific Databricks-based project successes to align with their technology partnership.
    β€” β€œExperience working with Databricks-based cloud data engagements specifically”
  • Demonstrate how you’ve mentored technical teams or led initiatives beyond standard project management.
    β€” β€œExperience mentoring technical teams or leading technical initiatives”
  • Showcase experience in AI/ML data ecosystems to align with their machine learning product focus.
    β€” β€œKnowledge of AI/ML data ecosystems”
  • Provide examples of managing end-to-end project delivery with clear risk and governance structures.
    β€” β€œEnd-to-end project planning & delivery – Define scope, objectives, and project plans”
Pace Β· Fast PacedCollaboration Β· HighAutonomy Β· MediumDecision Impact Β· TeamLevel Β· Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • end-to-end project planning and delivery
  • leading cross-functional teams
  • risk management and governance
  • quality and continuous improvement
Typical background
IT experience managing deliverycloud data engagements

Skills & requirements

Required

Project ManagementCloud Data StacksData EngineeringData MigrationData Lake/data Warehouse BuildsData Science ProjectsPM Tools And Techniques

Preferred

Machine LearningDemand PlanningBudget ForecastingRecommendation ModelsVisual Recognition

Stack & domain

PythonSparkAWSAzureGCPJiraTrelloZoho ProjectsRedmineLeadershipCommunicationData EngineeringCloud Data StacksMachine LearningData ProductsData Science

About the role

Original posting from Muttdata via Lever

πŸš€ Join Our Remote Data Products & Machine Learning Startup! πŸš€

At Muttdata, we build innovative Data Products and Machine Learning solutions that help companies solve complex business challenges. As a fast-growing, remote-first startup, we're passionate about technology, collaboration, and continuous learning.

We are looking for a proactive, hands-on, and business-orientedΒ Data Engineering Project ManagerΒ  to join our team πŸΆπŸš€. We're seeking someone with strong leadership and communication skills, well-versed in project management methodologies, and with a solid understanding of technical concepts across modern cloud data stacks. Adaptability, problem-solving abilities, and the capacity to work under pressure are key to success in this role.

This role will own cloud data engagements end to endΒ  from planning to execution β€” ensuring proposed plans are built and delivered on time, on budget, and within scope, while leading cross-functional teams of data engineers, data scientists, and other technical professionals.

πŸš€ What We Do:

  • Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
  • Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
  • Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
  • Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
  • Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
  • Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.

🌟 Our Partnerships:

  • Amazon Web Services
  • Astronomer
  • Databricks

🌟 Our Values:

  • πŸ“Š We are Data Nerds
  • πŸ€— We are Open Team Players
  • πŸš€ We Take Ownership
  • 🌟 We Have a Positive Mindset

πŸ” Curious about what we’re up to? Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects we’re working on! πŸš€

Responsibilities πŸ€“:

  • End-to-end project planning & delivery – Define scope, objectives, and project plans with stakeholders, ensuring adherence to timeline, budget, and resources.
  • Team leadership – Assemble and lead cross-functional teams (data engineers, data scientists, etc.), assigning clear roles and tasks.
  • Tracking & reporting – Monitor progress, proactively catch deviations, and implement tracking/reporting mechanisms for stakeholders.
  • Risk management & governance – Establish governance structures, identify risks, and develop mitigation and contingency plans.
  • Quality & continuous improvement – Maintain project documentation, promote best practices, and stay current with cloud computing trends.

Required Skills πŸ’»:

  • Graduate or Postgraduate degree in Computer Science, Information Technology, or a related field.
  • 7-10+ years of IT experience managing delivery and interfacing with key project stakeholders.
  • At least 2 years of experience managing cloud data engagements such as data migration, data lake/data warehouse builds, data engineering, or data science projects.
  • Hands-on experience with modern cloud data stacks (e.g., Databricks, Spark, Python, AWS, Azure, GCP).
  • Hands-on knowledge of PM tools and techniques (Jira, Trello, Zoho Projects, Redmine, or similar).
  • Experience implementing and managing Agile engineering project best practices.
  • Experience in strategic planning, risk management, and/or change management.
  • Strong written and spoken English.

Nice to have πŸ’‘:

  • Experience working with Databricks-based cloud data engagements specifically.
  • Experience working with financial services or other regulated industry clients.
  • Background in consulting environments or managing multiple concurrent clients.
  • Knowledge of AI/ML data ecosystems.
  • Experience mentoring technical teams or leading technical initiatives.

Perks🎁:

  • Remote-first culture – work from anywhere! 🌍
  • AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered.
  • Birthday off + an extra vacation week (Mutt Week! πŸ–οΈ)
  • Referral bonuses – help us grow the team & get rewarded!
  • Maslow: Monthly credits to spend in our benefits marketplace.
  • ✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!

Source: Muttdata careers (Lever)

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