ETL Data Integration Engineer

Summary

• Join our growing Data Engineering team to design, develop, and maintain enterprise-grade ETL and data integration solutions that support analytics, reporting, and business intelligence initiatives. You will build scalable data pipelines, develop robust data models, and integrate data from multiple enterprise systems. Candidates with strong ETL development, SQL/PL-SQL, data modeling, and data integration expertise are encouraged to apply. Experience with cloud platforms and modern data engineering tools is a plus.
• Key Responsibilities
• Design, develop, and maintain scalable ETL/ELT pipelines for enterprise data integration.
• Analyze business and technical requirements to create data mappings, transformation logic, and ETL specifications.
• Integrate data from multiple enterprise applications, databases, APIs, flat files, and cloud-based data sources.
• Develop and optimize data models to support reporting, analytics, and downstream applications.
• Build reliable and secure data ingestion processes using JDBC, REST APIs, Kafka, and other integration technologies.
• Implement data validation, reconciliation, and audit processes to ensure data quality, completeness, and consistency.
• Monitor, troubleshoot, and optimize ETL workflows for performance, scalability, and reliability.
• Support production ETL jobs by resolving failures, performing root cause analysis, and implementing preventive solutions.
• Collaborate with Business Analysts, Data Architects, Application Developers, and Infrastructure teams throughout the project lifecycle.
• Maintain technical documentation, data lineage, and ETL design standards.
• Participate in Agile (Scrum/Kanban) ceremonies, sprint planning, estimation, and code reviews.
• Follow data governance, security, and best practices for enterprise data management.
• Required Qualifications
• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline (or equivalent experience).
• 6+ years of experience in ETL development, data integration, or data engineering.
• Strong hands-on experience with SQL and PL/SQL.
• Proven experience designing, developing, and optimizing ETL pipelines and enterprise data integration solutions.
• Experience working with ETL tools such as Informatica, Talend, SSIS, Azure Data Factory, IBM DataStage, or similar technologies.
• Strong understanding of relational databases including Oracle, SQL Server, PostgreSQL, or MySQL.
• Experience with data modeling concepts including Star Schema, Snowflake Schema, Fact and Dimension modeling.
• Knowledge of data quality, reconciliation, and validation techniques.
• Excellent analytical, troubleshooting, and problem-solving skills.
• Strong verbal and written communication skills with the ability to work across cross-functional teams.
• Preferred Qualifications
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Knowledge of Apache Kafka, event-driven architecture, and real-time data integration.
• Experience with Python, Shell scripting, or automation frameworks.
• Familiarity with Spark, Databricks, or PySpark.
• Experience with Airflow, Control-M, Autosys, or other workflow orchestration tools.
• Exposure to CI/CD pipelines and DevOps practices.
• Experience working with Data Warehouses such as Snowflake, Redshift, Synapse, or BigQuery.
• Knowledge of Process Mining platforms such as Celonis is a plus but not required.
• What We're Looking For
• Strong expertise in ETL development, SQL/PL-SQL, and enterprise data integration.
• Ability to design scalable, high-performance, and reliable data pipelines.
• Passion for solving complex data integration challenges and improving data quality.
• Self-driven professional who can work independently while collaborating effectively within cross-functional teams.
• Candidates with strong ETL and Data Engineering experience who do not have exposure to specific tools like Celonis are encouraged to apply.