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Data Engineer

Infosys · Pune, India

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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.
  • Strong 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). Education Master Of Engineering,Master Of Technology,Bachelor of Engineering,Bachelor Of Technology