Job Description:
We are looking for a skilled and motivated
Data Engineer to join our dynamic team. As a Data Engineer, you will be responsible for designing, developing, and maintaining the infrastructure required for efficient collection, storage, and analysis of large-scale data sets. You will work closely with data scientists, analysts, and other stakeholders to ensure data availability, reliability, and performance, enabling the organization to make informed decisions.
Key Responsibilities:
- Data Infrastructure Development:
- Design, build, and maintain scalable data pipelines to ingest, process, and transform large datasets from multiple sources.
- Implement data storage solutions, such as data lakes, warehouses, and cloud-based systems, ensuring they meet business needs.
- Data Management & Governance:
- Develop and maintain ETL (Extract, Transform, Load) processes for moving data between systems.
- Ensure data integrity, quality, and consistency across platforms, implementing best practices for data governance.
- Collaboration & Integration:
- Collaborate with data scientists, analysts, and other teams to understand their data requirements and translate them into technical solutions.
- Integrate data from various internal and external data sources, including APIs, databases, and third-party systems.
- Performance & Optimization:
- Monitor data infrastructure performance, identifying areas for optimization and cost-saving opportunities.
- Implement data partitioning, indexing, and optimization techniques to improve query and data processing performance.
- Security & Compliance:
- Ensure that data architecture meets all security and compliance requirements, including data privacy standards such as GDPR.
- Develop and enforce policies for data access and usage, maintaining audit logs and other compliance records.
- Innovation & Continuous Improvement:
- Stay updated on emerging data engineering technologies, frameworks, and best practices.
- Contribute to the improvement of data processes, automation, and tooling across the organization.
Job Category: Data Engineer
Job Type: Full Time
Job Location: Pune
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Key Responsibilities:
- Data Infrastructure Development:
- Design, build, and maintain scalable data pipelines to ingest, process, and transform large datasets from multiple sources.
- Implement data storage solutions, such as data lakes, warehouses, and cloud-based systems, ensuring they meet business needs.
- Data Management & Governance:
- Develop and maintain ETL (Extract, Transform, Load) processes for moving data between systems.
- Ensure data integrity, quality, and consistency across platforms, implementing best practices for data governance.
- Collaboration & Integration:
- Collaborate with data scientists, analysts, and other teams to understand their data requirements and translate them into technical solutions.
- Integrate data from various internal and external data sources, including APIs, databases, and third-party systems.
- Performance & Optimization:
- Monitor data infrastructure performance, identifying areas for optimization and cost-saving opportunities.
- Implement data partitioning, indexing, and optimization techniques to improve query and data processing performance.
- Security & Compliance:
- Ensure that data architecture meets all security and compliance requirements, including data privacy standards such as GDPR.
- Develop and enforce policies for data access and usage, maintaining audit logs and other compliance records.
- Innovation & Continuous Improvement:
- Stay updated on emerging data engineering technologies, frameworks, and best practices.
- Contribute to the improvement of data processes, automation, and tooling across the organization.
Job Category: Data Engineer
Job Type: Full Time
Job Location: Pune
Key Responsibilities:
- Data Infrastructure Development:
- Design, build, and maintain scalable data pipelines to ingest, process, and transform large datasets from multiple sources.
- Implement data storage solutions, such as data lakes, warehouses, and cloud-based systems, ensuring they meet business needs.
- Data Management & Governance:
- Develop and maintain ETL (Extract, Transform, Load) processes for moving data between systems.
- Ensure data integrity, quality, and consistency across platforms, implementing best practices for data governance.
- Collaboration & Integration:
- Collaborate with data scientists, analysts, and other teams to understand their data requirements and translate them into technical solutions.
- Integrate data from various internal and external data sources, including APIs, databases, and third-party systems.
- Performance & Optimization:
- Monitor data infrastructure performance, identifying areas for optimization and cost-saving opportunities.
- Implement data partitioning, indexing, and optimization techniques to improve query and data processing performance.
- Security & Compliance:
- Ensure that data architecture meets all security and compliance requirements, including data privacy standards such as GDPR.
- Develop and enforce policies for data access and usage, maintaining audit logs and other compliance records.
- Innovation & Continuous Improvement:
- Stay updated on emerging data engineering technologies, frameworks, and best practices.
- Contribute to the improvement of data processes, automation, and tooling across the organization.
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