Data Engineer

Infosys; Pune District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Infosys is seeking a skilled Data Engineer in Pune to design and optimize scalable data pipelines and platforms. The role requires strong data modeling, cloud experience with Azure, Snowflake, and Databricks, and hands-on SQL/Python development to support data-driven decisions.

You will build robust ETL/ELT pipelines, manage data models, and ensure data quality across diverse data sources. Collaboration with analysts, scientists, and stakeholders is essential in this dynamic environment.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Systems, or related field.
• Strong experience in data engineering and data platform development.

Responsibilities

• Design, build, and optimize scalable data pipelines and data platforms.
• Develop and maintain data models using modern tools (DBT preferred).
• Write and optimize SQL queries across Snowflake, Azure SQL, and Synapse.
• Work with Azure data services including ADF, ADLS, Synapse, and Azure SQL Database.
• Develop data transformation scripts in Python (pandas, pyodbc, SQLAlchemy).
• Collaborate with cross-functional teams including data analysts, data scientists, and business stakeholders.

Skills

Data engineering

SQL

Python

ETL/ELT

Education

Bachelor's or Master's in CS/IS or related

Tools

Databricks

Snowflake

Azure Data Factory

Azure Synapse

ADLS

Azure SQL

Job description

Educational Requirements

• Bachelor of Engineering, Bachelor Of Technology, Master Of Technology, Master Of Engineering

Service Line

• Engineering Services

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.

• 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:
    • Azure Data Factory (ADF)
    • Azure Data Lake Storage (ADLS)
    • Azure Synapse Analytics
    • Azure SQL Database
  • Integrate and maintain Snowflake with Azure ecosystem.
• Python Development
  • Develop data transformation and automation scripts using Python libraries: pandas, pyodbc, 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

• Bachelors or Masters degree in Computer Science, Information Systems, or related field.
• Strong experience in data engineering and data platform development.

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).

Technical and Professional Requirements:

• Technical Skills
  • Expertise in DBT (preferred) for data modeling.
  • Strong SQL skills with hands-on experience in:
    • Snowflake
    • Azure SQL
    • Stored procedures
  • Proficiency in Python for data engineering workflows.
  • Hands-on experience with:
    • Databricks PySpark
    • 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.

Preferred Skills:

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