Senior ETL/Database Developer

Key Responsibilities :

ETL Development : Design, develop, and implement ETL workflows to extract data from various sources, transform it as needed, and load it into data warehouses or databases.

Data Integration : Integrate data from multiple systems, ensuring data consistency, accuracy, and reliability across all platforms.

Database Management : Develop and maintain complex queries, stored procedures, triggers, and functions within relational databases (e.g., SQL Server, Oracle, MySQL).

Data Modeling : Create and manage logical and physical data models, ensuring they meet business requirements for reporting, analytics, and performance.

Performance Optimization : Identify performance bottlenecks in data processes and optimize SQL queries, ETL jobs, and databases to ensure efficient data flow.

Collaboration : Work closely with business analysts, data scientists, and other team members to understand data requirements and ensure that the data is structured and formatted as per the business needs.

Data Quality : Ensure data integrity, accuracy, and consistency by implementing validation checks, error handling, and automated monitoring processes.

Documentation : Document ETL processes, database schemas, and troubleshooting procedures for future reference and knowledge sharing.

Troubleshooting and Maintenance : Monitor, troubleshoot, and resolve any issues related to ETL processes, databases, or data inconsistencies in a timely manner.

Version Control : Utilize version control systems (such as Git) to manage code and database scripts.

Required Skills and Qualifications :

Education : Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.

Experience :

3+ years of experience in ETL development, database development, or related roles.

Hands-on experience with ETL tools such as Informatica, Talend, Apache Nifi, or SSIS .

Proficiency in SQL for writing complex queries, stored procedures, and performance tuning.

Experience working with relational databases such as SQL Server, MySQL, or Oracle .

Familiarity with data modeling and schema design.

Experience with cloud-based data platforms like AWS, Azure, or Google Cloud is a plus.

Skills

• Strong understanding of ETL processes and data transformation techniques.

• Proficient in performance tuning and query optimization.

• Ability to troubleshoot, debug, and resolve database and data issues.

• Knowledge of scripting languages (e.g., Python, Shell scripting) is a plus.

• Familiarity with data warehousing concepts and data lakes.

• Good understanding of version control practices and Git.

Preferred Qualifications

• Familiarity with Big Data technologies (e.g., Hadoop, Spark).

• Experience in building and maintaining data pipelines using tools like Apache Airflow, Kafka, or AWS Glue .

• Knowledge of Data Governance principles and practices.