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DATAPAO

Cloud, data engineering, and analytics services

Engineering Manager - Data

Engineering LeadershipUpdated on Nov 11
Full-timeRemote in Spain

About the Job

Requirements

  • A consultant mindset and a focus on customer experience, including advising customers on appropriate technical solutions.
  • Strong software engineering foundations, including understanding distributed systems and familiarity with software engineering principles.
  • Experience contributing to teams that designed and implemented data-intensive applications, with hands-on SQL and NoSQL experience.
  • Ability to solve problems independently, advise others, and identify organizational gaps in processes, documentation, customer communication, or resource allocation.
  • Readiness to lead and support a team, based on team management or informal leadership experience such as leading project teams or owning delivery for a group.
  • Experience or interest in mentoring colleagues and supporting their goals and development plans.
  • Experience or readiness to help build teams and culture through hiring, onboarding, collaboration, or process improvement.
  • Ability to communicate technical concepts to varied audiences and maintain transparent communication across organizational levels.

Responsibilities

  • Lead a data engineering team of 5–6 consultants, taking over an existing team or building a new team depending on business needs.
  • Oversee project delivery and support successful execution of data engineering, machine learning, machine learning operations, and cloud migration projects for EMEA customers.
  • Split time between team management and hands-on project delivery.
  • Build and optimize scalable, high-performance data pipelines for data movement, transformation, and storage in enterprise customer environments.
  • Design, implement, and maintain ETL/ELT workflows, ingesting structured, semi-structured, and unstructured data from systems such as Oracle, Snowflake, and Redshift.
  • Support batch and streaming big-data processing and use data storage formats such as Delta Lake, Iceberg, and Hudi.
  • Collaborate with cloud, infrastructure, and data governance teams to support data reliability, observability, and monitoring.
  • Build enterprise data platforms, enable real-time and batch analytics workloads, and migrate legacy systems to modern cloud environments.

Desired Qualifications

  • Exposure to real-time data processing systems, Apache Spark, or the broader big data ecosystem.

About the Company

DATAPAO

Cloud, data engineering, and analytics services

Datapao provides Cloud, Data Engineering, and Data Science services that cover the full Data and Cloud Transformation journey from enablement through architecture to implementation. It designs and builds data and analytics systems to collect, store, and process data, creates analytics dashboards, and deploys production machine learning models to enable data-driven decisions, using platforms like Databricks, Azure, and AWS. It differentiates itself by offering end-to-end transformation support and industry-specific solutions across Manufacturing, Pharmaceuticals, Agriculture, Livestock, and Digital Products on a global scale. Its goal is to help clients unlock business value from data and cloud technologies to improve performance and outcomes.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
Budapest, Hungary
Founded
2016

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