Database Project Manager

Perficient; Chennai; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Perficient in Chennai is seeking an experienced Project Manager to lead data engineering, data warehouse, and ETL initiatives. You will drive delivery using Agile, Scrum, Waterfall or hybrid methods and coordinate cross-functional teams.

Strong hands-on with Jira, Azure DevOps, and MS Project; PMP/PRINCE2 or Scrum certifications preferred. 8+ years IT, 3+ years PM required. This role offers exposure to cloud data platforms and modern analytics workloads.

Qualifications

• 8+ years of overall IT experience with 3+ years in Project Management.
• Strong experience delivering Data Engineering, Data Warehouse, or ETL projects.
• Expertise in Agile, Scrum, Waterfall, and Hybrid delivery methodologies.
• Experience with Jira, Azure DevOps, MS Project, or similar PM tools.
• PMP, PRINCE2, or Scrum certifications preferred.

Skills

Project management

Data engineering delivery

Agile methodologies

Scrum

Waterfall

Hybrid delivery

PM tools experience

Education

PMP Certification

PRINCE2 Certification

Scrum Certification

Tools

Jira

Azure DevOps

MS Project

Job description

Required Skills & Qualifications Project Management

• 8+ years of overall IT experience with 3+ years in Project Management.
• Strong experience delivering Data Engineering, Data Warehouse, or ETL projects.
• Expertise in Agile, Scrum, Waterfall, and Hybrid delivery methodologies.
• Experience with Jira, Azure DevOps, MS Project, or similar PM tools.
• PMP, PRINCE2, or Scrum certifications preferred.
  

Data Engineering & ETL

• Strong understanding of:

  • ETL/ELT processes
  • Data Warehousing concepts
  • Data Modeling
  • Data Governance
  • Data Quality frameworks

• Experience working with:

  • SQL
  • Data Integration tools (Informatica, Talend, SSIS, DataStage)
  • Cloud data platforms

Cloud & Big Data (Preferred)

• Azure Data Factory
• Azure Synapse Analytics
• Databricks
• Snowflake
• AWS Glue
• Redshift
• Google BigQuery

Technical Knowledge

• Understanding of Data Pipelines and Workflow Orchestration.
• Exposure to Python, Spark, and Automation frameworks.
• Familiarity with CI/CD processes and DevOps practices.