Data Engineering Consultant
New
J
JobgetherData Engineering
Based in IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 9+ years
- Required Skills
- AWSPythonGCPSnowflakeAzureDatabricks
Requirements
- 9+ years of experience in data engineering, data architecture, analytics consulting, or related technology roles.
- 5+ years of hands-on experience implementing platforms such as Snowflake, Databricks, Amazon Redshift, or Azure Synapse Analytics.
- Strong experience with cloud platforms including AWS, Azure, or Google Cloud Platform.
- Proven expertise with ETL/ELT tools, including Fivetran, Alteryx, or similar data integration technologies.
- Experience designing data lake and lakehouse architectures and supporting both batch and real-time data pipelines.
- Advanced SQL skills and strong programming knowledge in Python, including libraries such as Pandas, NumPy, and Matplotlib.
- Good understanding of data governance, security practices, and compliance frameworks.
- Experience leading teams, technical workstreams, or consulting engagements in global delivery environments.
- Strong communication skills for collaborating with technical teams, business stakeholders, and executive audiences.
- MBA, Bachelor’s degree, or higher qualification in Engineering, Data Science, Information Systems, Mathematics, or a related field.
Responsibilities
- Design and deliver scalable data platforms, analytics solutions, and modern data architectures for global clients.
- Develop and optimize data solutions using technologies such as Snowflake, Databricks, Amazon Redshift, and Azure Synapse Analytics.
- Build and maintain efficient ETL/ELT workflows using tools such as Fivetran, Alteryx, and other data integration platforms.
- Design data lake and lakehouse architectures to support batch and real-time data processing requirements.
- Work with cloud platforms including AWS, Azure, and GCP to build secure and reliable data environments.
- Develop data pipelines, optimize performance, and ensure solutions meet scalability and reliability standards.
- Apply best practices in data governance, security, compliance, and data quality management.
- Collaborate with business leaders, technical teams, and stakeholders to translate requirements into effective data solutions.
- Lead technical discussions, guide delivery teams, and support client-facing consulting engagements.
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