Senior Data Engineer - ETL Development

Key Responsibilities :

- Design, develop, and maintain robust ETL/ELT workflows to ingest, transform, and load data from multiple structured and unstructured data sources.

- Build scalable and high-performance data pipelines to support business intelligence, analytics, machine learning, and reporting requirements.

- Develop and optimize data integration processes ensuring data quality, consistency, accuracy, and reliability.

- Design and implement data warehouse solutions, data marts, and dimensional models using industry best practices.

- Perform data profiling, cleansing, validation, and reconciliation activities.

- Monitor ETL jobs and troubleshoot performance bottlenecks, failures, and data quality issues.

- Collaborate with business analysts, data architects, data scientists, and application teams to understand data requirements and deliver effective solutions.

- Implement automation, scheduling, and monitoring mechanisms for ETL processes.

- Optimize SQL queries, database performance, and data processing workloads.

- Develop and maintain technical documentation, data dictionaries, lineage documentation, and operational procedures.

- Ensure compliance with data governance, security, privacy, and regulatory requirements.

- Participate in architecture discussions and contribute to data platform modernization initiatives.

- Mentor junior data engineers and promote best practices in data engineering and ETL development.

Required Skills & Qualifications :

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

- 5 to 10 years of experience in Data Engineering, ETL Development, or Data Warehousing.

- Strong experience in designing and developing ETL/ELT pipelines.

- Proficiency in SQL with expertise in query optimization and performance tuning.

Hands-on experience with ETL tools such as :

1. Informatica PowerCenter

2. Talend

3. SSIS

4. DataStage

5. Matillion

6. Apache NiFi

7. dbt

8. Azure Data Factory (ADF)

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

- Strong understanding of data warehousing concepts, dimensional modeling, star schema, and snowflake schema.

- Experience with cloud platforms such as AWS, Azure, or GCP.

- Hands-on experience with big data technologies such as Spark, Hadoop, Databricks, or Kafka is preferred.

- Proficiency in Python, Shell Scripting, or other programming languages used for data processing.

- Experience with version control systems such as Git.

- Knowledge of CI/CD practices and DevOps principles for data engineering.