Mphasis - Senior Data Engineer - Snowflake DB/Redshift (8-10 yrs)

Responsibilities :

- Design, develop, and maintain high-performance data pipelines using industry-leading tools like Snowflake, Redshift, BigQuery, DBT, and cloud platforms such as AWS (S3, Glue, Airflow), Azure (ADLS, ADF), or GCP.

- Develop and implement efficient data ingestion processes, data models (relational and dimensional), and data transformations.

- Collaborate closely with business stakeholders and data analysts to understand their data requirements and translate them into robust technical solutions.

- Implement end-to-end ETL/ELT workflows to seamlessly extract, transform, and load data from various sources into data warehouses and data lakes.

- Optimize data pipelines for performance, scalability, and cost-effectiveness.

- Conduct thorough data quality assessments and implement robust data governance best practices.

- Monitor and troubleshoot data integration processes to ensure the accuracy and integrity of data.

- Stay abreast of the latest advancements in data engineering technologies and best practices.

- Contribute to the development and improvement of data engineering processes and methodologies.

Qualifications :

- 8+ years of professional experience in building and managing data-related solutions, preferably within the financial industry.

- Strong proficiency in SQL and experience with at least one of the following data warehousing platforms: Snowflake, Redshift, BigQuery.

- Expertise in data modeling, including both relational and dimensional modeling techniques.

- Strong experience with cloud infrastructure and data platforms, such as AWS (S3, Glue, Airflow), Azure (ADLS, ADF), or GCP.

- Experience with data integration tools like DBT, Apache Airflow, or similar.

- Proven ability to design, develop, and maintain complex data pipelines.

- Experience with data quality assessment and data governance best practices.

- Excellent analytical and problem-solving skills.

- Strong communication and collaboration skills.

- A passion for data and a strong desire to learn and grow within the data engineering field.

Bonus Points :

- Experience with data streaming and real-time data processing technologies.

- Experience with machine learning and artificial intelligence applications.

- Experience with data visualization and business intelligence tools.

- Contributions to open-source projects or the data engineering community