Quess IT Staffing | Data Engineer | india
1 week ago
**Hiring**
Role:Data Engineer
Location:Hyderabad, bangalore, Pune, Gurgram, Mumbai, kolkata, Chennai.
Experience:5-7 Years
Notice period:Immediate - 15 Days
Job Description:
Must Skills:
Data Engineer expertise in SPARQL, graph technology
Job Summary: As a Data Engineer with expertise in SPARQL, Prophecy, general graph technologies, orchestration, and Python, you will be responsible for designing, building, and maintaining data pipelines and architectures to support advanced data analytics and business intelligence initiatives. You will leverage your technical skills to integrate, transform, and manage data from various sources, ensuring data quality, consistency, and accessibility. Your role will involve collaborating with data scientists, analysts, and other stakeholders to deliver robust data solutions that drive business insights and decision-making.
Key Responsibilities:
1. Data Pipeline Development -
Design, develop, and maintain scalable data pipelines using Python and other relevant technologies.
Implement data integration processes to collect, clean, and transform data from various sources.
Ensure data pipelines are optimized for performance, reliability, and scalability.
2. Graph Technology Implementation -
Utilize general graph technologies to model and manage complex data relationships.
Develop and maintain graph databases, ensuring efficient data storage and retrieval.
Implement SPARQL queries to extract and manipulate data from graph databases.
3. Data Orchestration -
Design and implement data orchestration workflows to automate data processing tasks.
Use orchestration tools (e.g., Apache Airflow, Prefect) to schedule, monitor, and manage data workflows.
Ensure data workflows are resilient, fault-tolerant, and well-documented.
4. Data Quality and Governance -
Implement data quality checks and validation processes to ensure data accuracy and consistency.
Develop and enforce data governance policies and procedures to maintain data integrity.
Monitor data pipelines and workflows to identify and resolve data quality issues.
5. Collaboration and Communication -
Work closely with data scientists, analysts, and business stakeholders to understand data requirements and deliver appropriate solutions.
Communicate technical concepts and solutions to non-technical stakeholders in a clear and concise manner.
Provide training and support to team members on data engineering best practices and technologies.
6. Continuous Improvement -
Stay updated with the latest advancements in data engineering, graph technologies, and orchestration tools.
Evaluate and recommend new tools, technologies, and methodologies to enhance data engineering capabilities.
Contribute to the continuous improvement of data management strategies and practices.
7. Prophecy Platform Utilization -
Leverage the Prophecy platform to design and manage data workflows and transformations.
Ensure seamless integration of Prophecy with existing data infrastructure and tools.
Optimize Prophecy workflows for performance and scalability.
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