Source

Global data ecosystem linking intelligence providers

Data Engineer

Data EngineeringConfirmed live in the last 24 hours

Full-timeVilnius, Vilnius City Municipality, Lithuania€3.5k - €5k /moHybrid

About the Job

Requirements

Proficiency in at least one programming language, ideally Python.
Experience with cloud infrastructure, ideally Google Cloud or AWS.
Knowledge of DataOps practices and tools including version control systems such as Git, Terraform, Docker, Kubernetes, and CI/CD.
Excellent SQL knowledge and understanding of data modelling and data warehousing principles.
A structured approach to problem solving, clear and concise communication, a high degree of ownership, attention to detail, and troubleshooting ability.
Fluency in written and spoken English and Lithuanian.

Responsibilities

Architect and maintain robust data models by analyzing the data ecosystem and defining clear relationships between data sources.
Engineer and optimize scalable, high-performance data pipelines using Google Cloud Platform and Airflow.
Translate business logic into efficient transformations while maintaining standards for data quality and system reliability.
Develop internal applications, automations, and reverse ETLs using Python.
Collaborate with cross-functional teams to identify automation opportunities and translate business challenges into scalable technical solutions.

Desired Qualifications

Familiarity with agent frameworks such as LangChain, Claude Agent SDK, or Google ADK, or workflow automation tools such as n8n.
Experience with event streaming platforms such as Kafka or Redpanda.
Proficiency in ClickHouse and other OLAP databases.
Technical aptitude and comfort with engineering-related discussions.

Source is an ecosystem of independent technology companies behind responsible access to web data. Source works behind the scenes, providing shared standards and dedicated support that help each company grow.
The culture follows the same idea: colleagues work across the ecosystem, share what they know, and hold a high bar, so a good idea in one place can create an advantage everywhere.

In this role, you will:

Architect and maintain robust data models by conducting thorough analysis of our complex data ecosystem to define clear relationships between data sources.

Engineer and optimize scalable, high-performance data pipelines using Google Cloud Platform and Airflow.

Translate complex business logic into efficient transformations while maintaining rigorous standards for data quality and system reliability.

Develop internal applications, automations, and reverse ETLs using Python.

Collaborate with cross-functional teams to identify automation opportunities and translate business challenges into scalable technical solutions.

Your skills & experiences:

Proficiency in at least one programming language, ideally Python.
Experience with cloud infrastructure (ideally Google Cloud or AWS).
Knowledge of best DataOps practices and tools including version control systems (e.g., Git), Terraform, Docker, Kubernetes, and CI/CD.
Excellent SQL knowledge and understanding of data modelling/data warehousing principles.
Structured mindset approach to problem solving, clear and concise communication, high degree of ownership, keen eye for detail and troubleshooting.
Fluency in English and Lithuanian, written and spoken.

Nice to have:

Familiarity with agent frameworks (e.g., LangChain, Claude Agent SDK, Google ADK) or workflow automation tools (e.g., n8n.io).

Experience with event streaming platforms, such as Kafka or Redpanda.

Proficiency in ClickHouse and other OLAP databases.

A technical aptitude and comfort with engineering-related discussions.

Salary & Benefits:

Gross salary: 3500 - 5000 EUR/month. Keep in mind that we are open to discuss a different salary based on your skills and competencies.

Growth & Learning: 40+ internal learning options, external conferences, mentorship, and year-round knowledge-sharing.

Health & Well-being: Private health insurance, psychotherapy, on-site well-being consultants, 24/7 gym access, and a wellness app.

Celebration & Community: Team events, an overseas workation, quarterly team-building budgets, and plenty of ways to mark milestones together.

Plus bonus vacation days, paid life-moment days off, barista coffee, and all the tools you need. See the full list of benefits here: https://source.ai/career/blog/benefits

Up for the challenge? Let’s talk!

About the Company

Source

Global data ecosystem linking intelligence providers

The company operates as a data ecosystem that connects several independent tech firms—Oxylabs, Decodo, Webshare, ScrapingBee, Honeygain, and upcoming ventures—under shared standards, strategic support, and a commitment to responsible access to data. Each member company runs its own team and product, but they collaborate through common intelligence and scale to serve a wider market. Their approach is to provide a networked set of data tools and services that collectively enable customers to access and use data more efficiently. The goal is to empower the next generation of data-powered products and decisions by offering interoperable capabilities and scalable data access while maintaining clear accountability for data use.

Company size: 501-1,000
Company stage: Not listed
Total funding: Not listed
Headquarters: Boston, MA
Founded: 2012

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