Data Engineer – Talend

About the Role We are looking for a Data Engineer with hands-on experience in Talend Data Integration to build and maintain scalable data integration pipelines. Working under senior data engineers and data architects, you will develop ETL/ELT jobs, support performance and reliability, and help ensure clean, validated, and well-governed data flows across enterprise systems. Key Responsibilities • Build and maintain ETL/ELT pipelines using Talend Data Integration • Develop data pipelines across multiple enterprise systems and heterogeneous data sources • Follow established best practices for pipeline design, error handling, logging, and reusability • Support optimisation of data workflows for performance and reliability (batch and near real-time) • Implement data quality, validation, and reconciliation controls within pipelines • Support job scheduling, orchestration, and deployment in on-premise environments • Work with data architects and senior engineers on metadata, standards, and documentation • Troubleshoot pipeline and data issues and support SLA adherence • Prepare and maintain pipeline documentation, source-to-target mappings, and operational notes Required Qualifications • 3–5 years of experience in data engineering / ETL development • Hands-on experience with Talend Data Integration and related components (Talend Studio, job design) • Good SQL skills — query writing, joins, aggregations, and basic performance tuning • Understanding of data modeling, data quality, validation, and reconciliation concepts • Experience with on-premise ETL job scheduling, deployment, and environment promotion • Ability to build maintainable, reusable, and reliable data pipelines • Good documentation, troubleshooting, and collaboration skills Tools & Technologies • ETL / Integration: Talend Data Integration (Talend Studio, Job Server, TAC) • Database / Querying: SQL, PostgreSQL or similar RDBMS • Version Control / Delivery: Git, GitLab, CI/CD basics • Scheduling / Orchestration: Talend Administration Center (TAC) / on-premise schedulers • Documentation: Pipeline mappings, data dictionaries, operational notes Good to Have • Proficiency in Python for data processing and automation • Exposure to orchestration tools such as Apache Airflow or Oozie • Exposure to data validation, reconciliation, staging, and metadata practices • Experience in secure, on-premise, air-gapped, or regulated/high-security environments • Familiarity with CI/CD-based deployment for ETL jobs Preferred Candidate Profile The ideal candidate is a hands-on Talend developer who can build and maintain reliable ETL pipelines, write solid SQL, validate and reconcile data, and work effectively under senior data engineers and architects in on-premise, governed environments.