Data Engineer (Databricks, Neo4j)

Datamaticstechnologies; Remote; EUR 70,000 - 90,000; Full time

Job summary

A leading technology company is seeking an experienced Data Engineer with a strong background in Databricks, Teradata, and Neo4j. This remote role requires candidates based in Europe. Responsibilities include designing data pipelines, optimizing ETL processes, and collaborating with cross-functional teams. The ideal candidate has 5-7 years of experience, mandatory skills in Databricks and Neo4j, and a solid understanding of cloud platforms. Join a global team focused on cutting-edge data technologies.

Qualifications

• 5–7 years of experience as a Data Engineer.
• Strong hands-on experience with Databricks.
• Mandatory expertise in Neo4j.

Responsibilities

• Design and optimize scalable data pipelines using Databricks.
• Build and maintain ETL/ELT processes across data environments.
• Integrate structured and unstructured datasets.

Skills

Databricks

Neo4j

Teradata

Python

Cloud platforms (Azure/AWS/GCP)

ETL/ELT concepts

Data modeling

Problem-solving

Communication skills

Tools

Spark

Kafka

Event Hub

Job description

Job Title: Data Engineer (Databricks, Teradata & Neo4j)

Location: Remote (Candidates must be based in Europe)

Experience: 5–7 Years

Employment Type: Full-Time

Client Location: Sweden

Position Overview

We are looking for an experienced Data Engineer with strong hands‑on expertise in Databricks, Teradata, and Neo4j to join a leading technology‑driven team in Sweden. This is a remote role, but we require candidates who are currently residing in Europe due to project compliance and collaboration needs. The ideal candidate will have a solid background in building scalable data pipelines, integrating complex data sources, and working with modern data platforms.

Key Responsibilities

Data Engineering & Development

• Design, develop, and optimize scalable data pipelines using Databricks (PySpark/Spark).
• Build, maintain, and enhance ETL/ELT processes across multiple data environments.
• Integrate structured and unstructured datasets for downstream analytics and consumption.
• Develop and optimize data models on Teradata for performance and reliability.
• Implement graph‑based data solutions using Neo4j.

Solution Design & Architecture

• Collaborate with solution architects and business teams to understand data needs and design robust solutions.
• Participate in system design sessions and contribute to architecture improvements.
• Ensure data quality, validation, and governance throughout the data lifecycle.

Performance & Optimization

• Troubleshoot and optimize Spark jobs, Teradata SQL queries, and data workflows.
• Ensure highly available and high-performance data pipelines.
• Monitor data operations and automate workflows where possible.

Collaboration & Communication

• Work with cross‑functional teams including BI, Data Science, and Platform Engineering.
• Document technical designs, pipelines, and solutions clearly and thoroughly.
• Communicate effectively with remote stakeholders in a multicultural environment.

Required Skills & Qualifications

• 5–7 years of experience as a Data Engineer.
• Strong, hands‑on experience with Databricks (Spark, PySpark, Delta Lake).
• Mandatory expertise in Neo4j (graph modeling, Cypher queries).
• Solid experience with Teradata (SQL, performance tuning, data modelling).
• Strong scripting and coding experience in Python.
• Experience working with cloud platforms (Azure/AWS/GCP) is preferred—Azure is a plus.
• Strong understanding of ETL/ELT concepts, data modelling, and distributed data processing.
• Excellent analytical, problem‑solving, and communication skills.
• Ability to work independently in remote, cross‑cultural teams.

Preferred Qualifications

• Experience with CI/CD pipelines for data workflows.
• Knowledge of data governance, data quality frameworks, and metadata management.
• Exposure to real‑time data processing technologies (Kafka, Event Hub, etc.) is an advantage.

Additional Information

• Remote role – Europe‑based candidates only due to project requirements.
• Opportunity to work with a global team on cutting‑edge data technologies.