Asks for

The ad says“Knowledge of workflow orchestration tools such as Apache Airflow, Prefect, or similar.”
The ad says“Proven experience with Apache Spark, or a similar distributed data processing framework.”
The ad says“Familiarity with other cloud-based data platforms and data services in AWS, Azure, or Google Cloud.”
The ad says“Familiarity with other cloud-based data platforms and data services in AWS, Azure, or Google Cloud.”
The ad says“Familiarity with data governance, metadata management, and data catalog solutions (e.g. Unity Catalog).”
The ad says“Strong SQL knowledge with hands-on experience in data modeling, querying, transformation, and optimization.”
The ad says“Experience using the Databricks Platform (Unity Catalog, Notebooks, SQL Warehouses, LakeFlow)”
The ad says“Fluent in English.”
The ad says“Fundamental usage of git-based code version control for python and SQL-based code-bases”
The ad says“Familiarity with other cloud-based data platforms and data services in AWS, Azure, or Google Cloud.”
The ad says“Native or fluent Greek, both written and spoken.”
The ad says“Minimum 4 years of experience in data engineering using at least one core language of Python, Scala, or Java.”
The ad says“Familiarity with data governance, metadata management, and data catalog solutions (e.g. Unity Catalog).”
The ad says“Knowledge of workflow orchestration tools such as Apache Airflow, Prefect, or similar.”
The ad says“Minimum 4 years of experience in data engineering using at least one core language of Python, Scala, or Java.”
The ad says“Minimum 4 years of experience in data engineering using at least one core language of Python, Scala, or Java.”
The ad says“Strong SQL knowledge with hands-on experience in data modeling, querying, transformation, and optimization.”
The ad says“Experience using the Databricks Platform (Unity Catalog, Notebooks, SQL Warehouses, LakeFlow)”

Values

The ad says“Experience with modern data warehouse technologies such as Snowflake, Amazon Redshift, Google BigQuery, or Azure Synapse.”
The ad says“Experience with streaming technologies such as Apache Kafka, Spark Streaming, or Apache Flink.”
The ad says“Experience with streaming technologies such as Apache Kafka, Spark Streaming, or Apache Flink.”
The ad says“Experience implementing CI/CD pipelines for data engineering workflows (e.g. Azure DevOps, Databricks Bundles).”
The ad says“Experience with modern data warehouse technologies such as Snowflake, Amazon Redshift, Google BigQuery, or Azure Synapse.”
The ad says“Knowledge of Infrastructure as Code such as Terraform, CloudFormation, or similar.”
The ad says“Experience implementing CI/CD pipelines for data engineering workflows (e.g. Azure DevOps, Databricks Bundles).”
The ad says“Experience using Lakehouse Catalog technologies (e.g. Delta, Iceberg) featuring data versioning, ACID and time-travel as well as performance tuning techniques (e.g. Liquid Clustering)”
The ad says“Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.”
The ad says“Experience with modern data warehouse technologies such as Snowflake, Amazon Redshift, Google BigQuery, or Azure Synapse.”
The ad says“Experience using Lakehouse Catalog technologies (e.g. Delta, Iceberg) featuring data versioning, ACID and time-travel as well as performance tuning techniques (e.g. Liquid Clustering)”
The ad says“Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.”
The ad says“Experience with modern data warehouse technologies such as Snowflake, Amazon Redshift, Google BigQuery, or Azure Synapse.”
The ad says“Experience with streaming technologies such as Apache Kafka, Spark Streaming, or Apache Flink.”
The ad says“Knowledge of Infrastructure as Code such as Terraform, CloudFormation, or similar.”

Incelligent builds Big Data, analytics, and AI/ML solutions that help enterprise and public sector organizations advance their digital transformation. Working across a diverse product portfolio, the team applies modern data-driven development practices to create production-ready software that brings together data engineering, analytics, and artificial intelligence for real-world use cases.

As a Data Engineer at Incelligent, you will contribute to Cloud-based data engineering initiatives that support robust, scalable data platforms and governance practices. This role is well suited to someone who enjoys working at the intersection of modern data infrastructure and applied innovation, with a particular focus on the Databricks platform, the Azure data ecosystem and the delivery of high-impact solutions for complex organizational environments.

Responsibilities

Design data lake zones, build, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
Work with relational databases, data warehouses, and data lakes as part of modern data platform delivery.
Translate responsibly business logic / analysis into production ready pipelines that deliver accurate results for critical business domains
Contribute to reusability initiatives, returning implementation assets back to the company to efficiently re-use it in future projects

Requirements

Minimum Requirements

Minimum 4 years of experience in data engineering using at least one core language of Python, Scala, or Java.
Strong SQL knowledge with hands-on experience in data modeling, querying, transformation, and optimization.
Proven experience with Apache Spark, or a similar distributed data processing framework.
Experience using the Databricks Platform (Unity Catalog, Notebooks, SQL Warehouses, LakeFlow)
Familiarity with data governance, metadata management, and data catalog solutions (e.g. Unity Catalog).
Experience designing, building, and maintaining scalable ETL/ELT pipelines for structured and unstructured data.
Experience working with relational databases, data warehouses, and data lakes.
Familiarity with other cloud-based data platforms and data services in AWS, Azure, or Google Cloud.
Knowledge of workflow orchestration tools such as Apache Airflow, Prefect, or similar.
Fundamental usage of git-based code version control for python and SQL-based code-bases

Nice to Have

MSc in Computer Science, Data Engineering, Data Science, Information Systems, Software Engineering, or a related field.
PhD or advanced specialization in Data Engineering, Computer Science, or a related field.
Experience with streaming technologies such as Apache Kafka, Spark Streaming, or Apache Flink.
Experience using Lakehouse Catalog technologies (e.g. Delta, Iceberg) featuring data versioning, ACID and time-travel as well as performance tuning techniques (e.g. Liquid Clustering)
Experience with data contracts, data quality checking automation using schema and value-matching techniques
Experience with modern data warehouse technologies such as Snowflake, Amazon Redshift, Google BigQuery, or Azure Synapse.
Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.
Experience implementing CI/CD pipelines for data engineering workflows (e.g. Azure DevOps, Databricks Bundles).
Knowledge of Infrastructure as Code such as Terraform, CloudFormation, or similar.

Other Qualifications

Fluent in English.
Native or fluent Greek, both written and spoken.
Eligible to work in Greece.

Benefits

Participation in state-of-the-art projects and tech challenges

Personal and professional development, amongst industry experts and talented people

Continuous learning, having access to broad resources for professional and personal development

Friendly environment and fun team member

Commitment to Equal Employment Opportunity: All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, disability, age, or other characteristics. We respect your personal data.

All personal information in your application and CV will remain strictly confidential.