MUMBAI · FULLTIME
Senior Data Engineer
Nuvama Group
Mumbai · onsite · Posted 6d ago
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Section · 01
About this role
We are hiring enthusiastic professionals who have zeal to turn data into information, information into insight and insight into business decisions also strong expertise in cloud-based data platforms and AI/ML technologies. Data Engineer would be responsible for developing and creating batch and data pipelines for ETL/ELT as per the User requirement. Data Engineer shall be responsible for leading the database related efforts (primarily MS SQL DWH and Redshift ) in the engagement which will include data warehousing, ETL, data modeling, database integration/migration, database development and database management efforts for the engagements. Experience: 5 to 7 years. Job Responsibilities:
- Architect, build, and maintain scalable, secure ETL/ELT pipelines for batch.
- Code, test, and deploy batch and data pipelines using PySpark, SQL, and Python.
- Developing scalable and re-usable, self-service frameworks for data ingestion and processing.
- Integrate AI/ML workflows into data engineering pipelines.
- Prepare, cleanse, and transform large datasets for machine learning models.
- Managing, implementation and regular monitoring of ETL activities right from Source systems to Power BI Layer using Azure and AWS cloud services
- Design distributed data lakes and data warehousing solutions using native cloud environments
- Track automated pipeline health in AWS Glue, Azure Data Factory, or Apache Airflow to fix failures. Coordinate with user group for issues/requirements
- Design scalable star and snowflake schemas for cloud data warehouses like AWS Redshift and Azure Synapse.
- Support for the existing project
- Bringing best practices in following areas: Design & Analysis, Automation (Pipelining etc.), Testing, Monitoring and Documentation. Preferred Background:
- Proficiency in Python or Scala for data processing.
- Strong expertise in cloud-based data platforms and AI/ML technologies.
- Good knowledge of Apache Spark, PySpark, and Hadoop, Familiar with AWS Services like Glue, S3, Athena etc.
- Machine Learning fundamentals and Generative AI applications.
- Azure services like ADF, ADLS, Synapse Analytics, Databricks.
- Power BI is optional.
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Section · 02