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# SL Transformation-Senior Data Engineer

- **Company:** Hays plc
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £111,800.0 - £115,180.0
- **Contract:** Temporary contract
- **Skills:** Agile Methodology, Airflow, Amazon Web Services, Microsoft Azure, Big Data, BigQuery, Continuous Integration, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Migration, Data Warehousing, DevOps, Distributed Computing Environment, Revision Control Systems, Python (Programming Language), SQL Databases, Data Streaming, Unstructured Data, Workflow Management Systems, Data Processing, Data Ingestion, Snowflake, Apache Spark, Data Lakes, Apache Kafka, Data Management, Azure Synapse Analytics, Data Pipelines, Serverless Computing, Amazon Redshift, Databricks
- **Published:** August 17, 2026
- **Apply:** https://www.careerboard.com/pt/en/find-jobs-in-United-Kingdom/-F5E8A4D7A98B232112/

## About the Role

* Strong experience in SQL and data modelling concepts.
 * Hands-on experience with ETL/ELT development.
 * Proficiency in Python, Scala, or Spark-based data processing.
 * Experience with cloud platforms such as AWS, Azure, or GCP.
 * Knowledge of Data Warehouse and Data Lake architectures.
 * Experience with orchestration tools such as Airflow, ADF, or equivalent.
 * Understanding of data governance, data quality, and security practices.
 * Familiarity with CI/CD pipelines and version control tools.

Preferred Skills

 * Experience with Databricks, Snowflake, Redshift, Synapse, or BigQuery.
 * Knowledge of Real Time streaming technologies such as Kafka.
 * Exposure to Agile delivery methodologies.
 * Experience in large-scale data transformation or modernization programs.
 * Expected Competencies
 * Strong analytical and problem-solving skills.
 * Excellent stakeholder communication and collaboration.
 * Technical leadership and mentoring capability.
 * Ability to work independently and drive delivery in a fast-paced environment.

## Description

* Design, develop, and maintain robust ETL/ELT pipelines for structured and unstructured data.
 * Build scalable data ingestion, transformation, and storage solutions using modern data engineering frameworks.
 * Develop and optimize data models, data warehouses, and lakehouse architectures.
 * Ensure data quality, integrity, security, and governance across data platforms.
 * Collaborate with business stakeholders, data analysts, architects, and product teams to understand requirements and deliver solutions.
 * Monitor and troubleshoot data pipelines, resolving performance bottlenecks and operational issues.
 * Implement CI/CD, automation, and DevOps practices for data engineering workflows.
 * Work with cloud-native services and distributed data processing technologies.
 * Support data migration and modernization initiatives as part of transformation programs.
 * Mentor junior engineers and contribute to technical best practices and standards.


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