Data Engineer (Contributor - Data & AI Products)

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1 month ago

Basic Information

Artificial intelligence and data are shaping the future – and you can be at the heart of this change! The new Data & AI Transformation Directorate / AI Transformation Tribe of the OTE Group is looking for people with vision, enthusiasm, and commitment to contribute to the Organization’s digital transformation.

If you want to actively contribute to the digital transformation of one of the largest organizations in Greece and leave your mark on projects and solutions that leverage the power of data and artificial intelligence to drive innovation, then this role is for you.

We are looking for Data Engineers who want to work in cross-functional product squads, build data pipelines (ETL/ELT), ensure data quality and observability by design, and collaborate closely with Data Scientists, ML Engineers, and Product Owners to deliver functional and reliable data products and AI solutions with measurable business impact.

Responsibilities

Design and implement end-to-end data pipeline and data product architectures (batch + streaming) for analytics/AI.
Participate in and/or technically lead data modeling activities for lakehouse/warehouse environments, ensuring performance, scalability, and cost efficiency.
Contribute to defining standards and best practices in data quality, testing, monitoring/observability, and data SLAs.
Collaborate closely with ML/AI teams on feature pipelines, dataset versioning, and building dependable data foundations for ML workflows.
Conduct code reviews and elevate the team’s overall engineering maturity.
Contribute to cross-squad alignment (shared datasets, governance).
Participate in incident handling and root-cause analysis for data issues, building prevention mechanisms.

Requirements

Engineering

Strong knowledge of advanced SQL (optimization, partitioning strategies, query tuning).
Strong knowledge of Python (and/or Scala/Java) for robust data processing.
Solid experience with ETL pipelines (e.g., DBT, Spark) and orchestration tools (e.g., Airflow/Dagster).
Hands-on experience with cloud data platforms (e.g., Azure or GCP Data Factory, Snowflake, Databricks, etc.).
Experience with streaming technologies (e.g., Kafka, Spark Structured Streaming, event-driven architectures).
Experience with data quality frameworks (e.g., Great Expectations or custom solutions) and observability practices.
Ability to translate business needs into technical designs, managing trade-offs (latency vs cost vs complexity).
Strong soft skills: stakeholder management, clarity in requirements, and technical leadership without a “command-and-control” approach.

Benefits

Bonus structure

Continuous education

Wellness programs

Bonus structure
Continuous education
Wellness programs

Good to have

Experience with Lakehouse patterns (Delta/Iceberg/Hudi) and governance.
Experience in DataOps / CI/CD for data (testing, deployment, environment promotion) using Jenkins and GitLab.
Knowledge of privacy and security principles (GDPR), data masking, access control, RBAC/ABAC.
Understanding of telecom data (CDRs, network events) or high-volume event analytics.

Data Engineer (Contributor - Data & AI Products)

Basic Information

Responsibilities

Requirements

Benefits

Good to have

Team

Recruitment process

About the company

About the company

Data Engineer (Contributor - Data & AI Products)

Basic Information

Responsibilities

Requirements

Benefits

Good to have

Team

Recruitment process

About the company

About the company