About the role
Job Summary:
We are seeking a skilled ETL & Database Engineer to design, develop, and maintain robust data pipelines and database solutions. The ideal candidate will have hands-on experience with ETL tools, SQL/NoSQL databases, and data warehousing concepts, ensuring high data quality and performance across systems.
Key Responsibilities:
- Design and implement ETL workflows to ingest, transform, and load data from various sources.
- Develop and optimize SQL queries, stored procedures, and database functions.(High Proficiency)
- Maintain and enhance data models and schemas for reporting and analytics.
- Monitor and troubleshoot data pipeline performance and reliability.
- Collaborate with data analysts, BI developers, and business stakeholders to understand data requirements.
- Ensure data integrity, security, and compliance with governance policies.
- Automate data validation and reconciliation processes.
- Document technical specifications, data flow diagrams, and operational procedures.
Required Skills & Qualifications:
- Bachelor's or Master’s degree in Computer Science, Information Systems, or related field.
- 5+ years of experience in ETL development and database management.
- Proficiency in ETL tools such as Informatica, Talend, SSIS, Apache NiFi, or equivalent.
- Strong SQL skills and experience with relational databases (e.g., Oracle, SQL Server, PostgreSQL, MySQL).
- Experience with cloud data platforms (e.g., AWS Redshift, Azure Synapse, Google BigQuery).
- Familiarity with NoSQL databases (e.g., MongoDB, Cassandra) is a plus.
- Knowledge of data warehousing concepts and dimensional modelling.
- Experience with version control systems (e.g., Git) and CI/CD pipelines.
- Excellent problem-solving and communication skills.
Preferred Qualifications:
- Design and implement ETL workflows to ingest, transform, and load data from various sources.
- Develop and optimize SQL queries, stored procedures, and database functions.(High Proficiency)
Good to have
Experience with Python or Scala for data processing.
Exposure to big data technologies (e.g., Hadoop, Spark).
Knowledge of data governance and data quality frameworks.