At Hays , we are collaborating with a integral manufacturer of metal components for the automotive industry , present in 22 countries with more than 40,000 employees. This industrial environment generates big volumes of data across heterogeneous sources ( SAP ERP, SCADA systems, MES platforms, IoT sensors, relational databases, and document stores ) that have to be reliably extracted, normalised, and made available for analytics, reporting, and AI workloads.

La experiencia que se espera de los solicitantes, así como las habilidades y cualificaciones adicionales necesarias para este trabajo, se enumeran a continuación.

We are currently looking for a Data Extraction Engineer who specialises in getting data out of complex source systems into the Azure-based lakehouse reliably and at scale. You will own the extraction and ingestion layer end-to-end, building robust pipelines that connect their operational systems to the Bronze layer of their Medallion architecture on Databricks.

What are the requirements?

- 4+ years of hands-on experience building data extraction and ingestion pipelines in production environments.
- Python proficiency for pipeline scripting, custom Airflow operators, and data validation logic.
- Strong SQL skills across multiple engines: SQL Server, PostgreSQL, Azure SQL, and SAP HANA (CDS Views a strong plus).
- Practical experience extracting from and integrating MongoDB : change streams, oplog-based CDC, schema flexibility handling.
- Proficiency with Apache Airflow: authoring complex DAGs, managing dependencies, handling retries, and monitoring pipeline health.
- Solid understanding of CDC patterns : log-based vs. query-based, Debezium, Kafka connectors, and Azure Event Hubs integration.




- Experience landing data into cloud lakehouse architectures ( Azure Data Lake + Delta Lake / Databricks).
- Advanced English communication skills (spoken and written).

Nice to have

- Experience extracting data from SAP (ABAP SDK, CDS Views, BAPI/RFC, OData) — highly valued.
- Familiarity with industrial data sources: SCADA historians, MES systems, OPC-UA, MQTT.
- Knowledge of DBT for downstream transformation layers.
- Experience in multi-plant or multi-country enterprise environments.
- Background in the automotive or discrete manufacturing sector.

What will your responsibilities be?

Data Extraction & Ingestion (core focus)

- Design and implement data extraction pipelines from SAP HANA (CDS Views, ABAP SDK) , relational databases (SQL Server, PostgreSQL, Azure SQL), document stores (MongoDB), and SCADA/MES/IoT platforms handling high‑frequency time‑series data.
- Build and maintain CDC pipelines from SAP and operational systems into Azure Data Lake Storage Gen2 using Apache Kafka / Azure Event Hubs .
- Develop API-based connectors for SaaS platforms (HR systems, quality tools, third‑party suppliers) according to business needs.
- Ensure accurate and complete ingestion into the Bronze layer (Delta format) with full metadata, lineage, audit trails, and extraction logging.

Pipeline Orchestration & Reliability

- Orchestrate ingestion workflows using Apache Airflow (MWAA or AKS) , ensuring pipelines are idempotent,



observable, and operationally robust.
- Implement monitoring, alerting, and SLA tracking to ensure data freshness and pipeline reliability.
- Manage incremental versus full-load strategies tailored to source system load, data volume, and latency requirements.
- Collaborate with Data Architecture teams to align the Bronze layer with downstream Silver and Gold processing on Databricks .

Data Quality at Source

- Apply data quality validations at ingestion , including completeness checks, schema and type validation, referential integrity, and duplicate detection.
- Document source system schemas, data models, data dictionaries, and known data quality issues.
- Work closely with IT teams and system owners to manage source system constraints, maintenance windows, and schema changes .

Collaboration & Documentation

- Partner with AI/ML and AI Agents teams to deliver curated datasets for analytics, RAG, and machine‑learning workloads.
- Produce and maintain technical documentation, including extraction specifications, data contracts, pipeline runbooks, and ADRs .
- Participate in architecture reviews and contribute to the data platform roadmap and continuous improvement initiatives.

What do we offer?

- Remote work model but with possibility of on-site/hybrid model.
- Location: Madrid (Headquarters).
- Full‑time freelance/permanent contract with Hays.

We are looking for professionals like you, passionate about technology, and eager to take on a new challenge. xcskxlj If this aligns with you, apply for the position so we can share more details with you!

Hay opciones de teletrabajo/trabajo desde casa disponibles para este puesto.

📌 Data Extraction Engineer (Remote) (Carballedo)
🏢 Talent
📍 Carballedo