Key Responsibilities:

- Role demands a highly skilled Data Engineer to design build and optimize scalable data pipelines and data platforms
- The ideal candidate will have strong expertise in data modeling cloud based data architectures and modern data engineering tools across Azure Snowflake and Databricks environments
- Key Responsibilities
- Data Engineering Pipeline Development
- Design develop and maintain robust ETL ELT pipelines using Databricks PySpark and Azure Data Factory ADF
- Build scalable and efficient data ingestion frameworks for structured and unstructured data
- Optimize pipeline performance through performance tuning and orchestration best practices
- Data Modeling Management
- Develop and maintain data models using modern tools DBT preferred
- Implement Master Data Management MDM solutions to ensure data consistency and integrity
- Design scalable and efficient Snowflake schemas star snowflake schema dimensional modeling
- Database Query Optimization
- Write and optimize advanced SQL queries across Snowflake Azure SQL and Synapse
- Develop and manage stored procedures and database objects
- Ensure efficient data retrieval through indexing partitioning and query optimization
- Cloud Platform Integration
- Work with Azure data services including
- o Azure Data Factory ADF
- o Azure Data Lake Storage ADLS
- o Azure Synapse Analytics
- o Azure SQL Database
- Integrate and maintain Snowflake with Azure ecosystem
- Python Development
- Develop data transformation and automation scripts using Python libraries
- o pandas
- o pyodbc
- o SQLAlchemy
- Build reusable components for data processing and validation
- Data Quality Validation Monitoring
- Implement data validation rules quality checks and anomaly detection frameworks




- Perform root cause analysis for data inconsistencies
- Develop dashboards or tools for data quality monitoring
- Collaboration DevOps
- Use GitHub for version control branching strategies and code reviews
- Manage workload scheduling and dependency management for pipelines
- Collaborate with cross functional teams including data analysts data scientists and business stakeholders
- Required Skills Qualifications
- Bachelor s or Master s degree in Computer Science Information Systems or related field
- Strong experience in data engineering and data platform development

Technical Requirements:

- Technical Skills
- Expertise in DBT preferred for data modeling
- Solid SQL skills with hands on experience in
- o Snowflake
- o Azure SQL
- o Stored procedures
- Proficiency in Python for data engineering workflows
- Hands on experience with
- o Databricks PySpark
- o Azure Data Services ADF ADLS Synapse
- Strong knowledge of Snowflake architecture and schema design
- Experience with data validation quality frameworks and analysis tools
- Familiarity with GitHub and CI CD practices

Additional Responsibilities:

- Preferred Qualifications
- Experience implementing data governance and MDM solutions
- Knowledge of performance tuning in distributed processing systems
- Familiarity with workflow orchestration tools
- Experience in agile environments SCRUM Kanban

Preferred Skills:

Technology->Data Engineering->Databricks,Technology->Cloud Integration->Azure Data Factory (ADF),Technology->Big Data - Data Processing->PySpark,Technology->Oracle->PL/SQL,Technology->Data on Cloud-DataStore->Snowflake,Technology->Cloud Platform->Databases on Azure->Azure SQL Database,Technology->Cloud Platform->Azure Analytics Services->Azure Data Lake

📌 Data Engineer (India)
🏢 Infosys
📍 India