Offer summary

Qualifications:

Minimum 4 years of experience in Data Engineering, with expertise in Azure DataBricks or similar cloud platforms., Strong skills in Python and SQL for data processing and pipeline development., Solid understanding of data modeling, data lifecycle, and best practices in software development (Git, CI/CD)., Excellent communication skills in English and ability to collaborate effectively with stakeholders..

Key responsibilities:

Design, develop, and maintain ETL pipelines using PySpark in Databricks.

Translate business needs into reliable, high-performance data solutions and insights.

Lead the technical vision for data engineering projects and mentor team members.

Manage Databricks assets and automate workflows using tools like GitHub Actions.

Job description

We are offering an exciting opportunity for you to get involved and work on a variety of projects. You will have the chance to join projects in their early stages, shape the technical direction, and take the initiative in building the necessary teams, creating an environment that fosters personal initiative and autonomous action. You will receive full support and guidance as you enhance your skills and develop new competencies with a focus on the Data Tech Lead perspective.

Challenges you'll tackle:

Translate business challenges into actionable, data-driven solutions
Collaborate with data engineers, analysts, and key stakeholders to effectively translate business needs into data-driven solutions
Leverage data insights to develop strategic recommendations aligned with business goals
Convert business requirements into reliable, high-performance data sets in Databricks Data Lakehouse
Design, develop, and maintain ETL pipelines using PySpark, ensuring efficient data processing and automation
Manage Databricks assets, utilizing Asset Bundles for structured resource organization
Automate deployment and workflows using GitHub Actions
Lead the technical vision, drive best practices in data engineering and cloud solutions, and mentor the team to align with business objectives and emerging technologies

Requirements

Skills for success:

Proven experience (4+ years) in Data Engineering with a strong focus on Azure DataBricks or similar expertise in cloud-based data engineering platforms (AWS, google)
Data-Driven Mindset: capability to convert business problems into data-driven solutions, utilizing data to drive decision-making and actionable insights
Knowledge of ML lifecycle
Expertise in data modeling at both the logical and physical levels, with the ability to optimize data structures
Knowledge of best practices in software development (Git, CI/CD)
Proficiency in Python and SQL
Exceptional verbal and written communication skills in English
Excellent collaboration and communication skills with a focus on stakeholder alignment and team mentorship

Nice to Have:

Experience with MLOps and model deployment in production environments
Understanding of data streaming (e.g., Kafka, Azure Event Hubs)

Benefits

Competitive Compensation & Growth Opportunities

Dedicated training budget for conferences, online courses, and books to support continuous learning
Access to English and Lithuanian language lessons
Professional development through workshops, coaching sessions, and tech events

Work-Life Balance & Flexibility

Flexible working hours to suit your schedule
Unlimited work-from-home option for greater autonomy

Community & Team Connection

Employee referral program with rewards up to 2000€ net
Clients & External Ambassadors with rewards up to 5000€ net
Social events, including Summer/Winter parties and a Dev Day celebration
Team-building activities and annual live meet-ups with clients for enhanced collaboration

For this position, we offer 4793 € - 5785 €/month gross salary.

The final offer will depend on your experience and competencies

Required profile