Part-Time Data Engineer - Azure And Data Factory Jobs Opening in Prachi solutions at Alwal, Hyderabad
Job Description
Job Title: Part-Time Data Engineer - Azure and Data Factory
More information about this Part-Time Data Engineer - Azure and Data Factory Job
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Location: Remote / Hybrid
Job Type: Part-Time
Experience Level: Mid to Senior
Job Summary:
We are seeking a highly skilled and motivated part-time Data Engineer with expertise in Azure Data Services, especially Azure Data Factory. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines and data integration solutions to support our analytics and business intelligence needs.
We are seeking a highly skilled and motivated part-time Data Engineer with expertise in Azure Data Services, especially Azure Data Factory. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines and data integration solutions to support our analytics and business intelligence needs.
Key Responsibilities:
• Design, develop, and maintain data pipelines using Azure Data Factory.
• Implement ETL/ELT processes to ingest and transform data from various sources (on-prem, cloud, APIs).
• Build and manage Azure Data Lake, Azure SQL Database, and other Azure data services.
• Optimize and monitor data pipelines for performance and reliability.
• Collaborate with analysts, data scientists, and stakeholders to understand data requirements.
• Ensure data quality, integrity, and security across all systems.
Requirements:
• 8+ years of experience in Data Engineering with a focus on Azure.
• Hands-on experience with Azure Data Factory, Azure Data Lake, Azure SQL, and Synapse Analytics.
• Strong knowledge of SQL, Python or PySpark for data transformation.
• Experience with CI/CD pipelines, version control (e.g., Git), and DevOps practices.
• Familiarity with data modeling, data warehousing, and data governance principles.
• Excellent problem-solving and communication skills.
Nice to Have:
• Experience with Power BI or other data visualization tools.
• Knowledge of Azure Purview, Databricks, or other big data tools.
• Azure certification (e.g., DP-203 – Azure Data Engineer Associate).
Work Schedule:
• Part-time: 15–20 hours/week
• Flexible timing with periodic team syncs
Compensation:
• Competitive hourly rate or monthly retainer (based on experience)
Contact us for more information
More information about this Part-Time Data Engineer - Azure and Data Factory Job
Please go through the below FAQs to get all answers related to the given Part-Time Data Engineer - Azure and Data Factory job
- What are the job requirements to apply for this Part-Time Data Engineer - Azure and Data Factory job position?
- Ans: A candidate must have a minimum of 3+ year experience as an Part-Time Data Engineer - Azure and Data Factory
- What is the qualification for this job?
- Ans: The candidate can be a Graduate from any of the following: B.Com, BE/B.Tech, CS
- What are the salary requirements for this job?
- Ans: The salary range is between 35000 and 70000 Monthly. The Salary will depend on the interview. This Part-Time Data Engineer - Azure and Data Factory is a Part Time in Hyderabad.
- What is the hiring Process of this job?
- Ans: The hiring process all depends on the company. Normally for an entry level, hiring the candidate has to go for Aptitude, GD (If they look for communication),Technical test and face to face interviews.
- This Part-Time Data Engineer - Azure and Data Factory is a work from home job?
- Ans: No ,its not a Work from Home Job.
- How many job vacancies are opening for the Part-Time Data Engineer - Azure and Data Factory position?
- Ans: There are immediate 1 job openings for Part-Time Data Engineer - Azure and Data Factory in our Organisation.
Job Particulars
Role data engineer
Who can apply Experienced (3+ Years)
Hiring Process Telephonic Interview, Virtual Interview
Employment TypePart Time
Job Id2666425
Job Category IT/Software , Core Technical , BSc/BCA/BBM , Finance
Locality Address Alwal
State Telangana
Country India
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