Senior Data Engineer

About the role

We are seeking a Senior Data Engineer to design, build, and optimise scalable data platforms, ETL/ELT pipelines and data warehouses that power analytics, AI and business applications. The ideal candidate combines strong software‑engineering fundamentals with cloud experience and a passion for delivering reliable, secure and high‑quality data solutions.

Key responsibilities

• Design, develop and maintain scalable ETL/ELT pipelines to ingest, process and transform data from diverse sources into data warehouses and data lakes.
• Build and optimise data models, database schemas and storage solutions for high‑performance processing.
• Manage relational (PostgreSQL, MySQL, SQL Server, Oracle) and NoSQL (MongoDB, Elasticsearch) databases, ensuring performance, scalability, security and integrity.
• Develop SQL objects – stored procedures, functions, triggers, views – and write efficient queries.
• Design and maintain OLTP and OLAP systems, including dimensional modelling and data‑warehouse architectures.
• Implement data validation, monitoring and quality‑assurance processes.
• Develop and integrate REST APIs for data ingestion and distribution.
• Automate workflows and orchestrate pipelines using Apache Airflow and related tools.
• Collaborate with software engineers, product managers and business stakeholders to deliver scalable data solutions.
• Participate in code reviews, CI/CD pipelines and Git‑based development workflows.

Required profile

• Bachelor’s degree in Computer Science, Information Technology, Data Science or a related field (preferred).
• 5+ years of professional experience in data engineering, software engineering or database development.
• Strong analytical and problem‑solving skills with a solid computing foundation.
• Experience delivering production‑grade data platforms on cloud providers (AWS, Azure or GCP).

Required skills

• Python and SQL (including PL/SQL or T‑SQL).
• Relational databases: PostgreSQL, MySQL, SQL Server, Oracle.
• NoSQL databases: MongoDB, Elasticsearch.
• Cloud services: AWS (S3, Redshift, Glue, Athena, RDS, Lambda), Azure, GCP (BigQuery).
• Containerisation and orchestration: Docker, Kubernetes.
• Workflow orchestration: Apache Airflow.
• Data transformation tool: DBT.
• Version control: Git.
• BI/visualisation tools: Power BI, Tableau (optional).
• REST API design and integration.