Data Architect - Jaipur

Deloitte India is hiring for Technical Project Manager with 6+ Years of experience

Notice Period - Immediate to 30 Days

Location : Comfortable working from Jaipur Location

Should have prior Government Experience.

What impact will you make?

Every day, your work will make an impact that matters, while you thrive in a dynamic culture of inclusion, collaboration and high performance. As the undisputed leader in professional services, Deloitte is where you’ll find unrivaled opportunities to succeed and realize your full potential

Deloitte is where you’ll find unrivaled opportunities to succeed and realize your full potential.

The Team

Deloitte Digital is passionate and focused on helping clients tackle their most complex challenges. Learn how we help clients innovate, improve user experience, and maximize the value from customer operations by harnessing the breadth and depth of our digital capabilities.

Minimum Experience and Qualifications:

1. BE/BTech/MCA
2. Minimum 10 years of experience in data engineering and architecture roles.
3. Proven expertise in building Data Lakes, Data Warehouses, Lakehouses, and Data Marts.
4. Strong expertise in data modeling, database design, and data management principles.
5. Hands-on experience with cloud platforms (AWS Redshift, Azure Synapse, GCP BigQuery, Snowflake, Databricks).
6. Proficiency in SQL, Python/Scala/Java, and distributed data processing frameworks (Hadoop, Spark, Kafka).
7. Experience with ETL/ELT tools (Informatica, IBM DataStage, Talend, dbt, etc.).
8. Solid understanding of data governance, MDM, metadata management, lineage, and security standards.
9. Proven track record in leading enterprise data transformation projects.
10. Strong communication and leadership skills with ability to work across technical and business teams.

Roles and Responsibilities:

1. Architect and implement enterprise-grade Data Lakes, Data Warehouses/Lakehouses, and Data Marts to support analytics, BI, and AI/ML use cases.
2. Design data models (conceptual, logical, physical) tailored for analytical and operational workloads.
3. Define and implement data ingestion, ETL/ELT pipelines, and integration strategies across multiple sources.
4. Ensure scalability, performance, and reliability of data platforms, enabling seamless self-service analytics.
5. Establish and enforce data governance, security, privacy, and compliance frameworks.
6. Optimize storage, query performance, and data lifecycle management across large-scale datasets.
7. Collaborate with business and technical teams to translate requirements into effective data architectures.
8. Provide technical leadership, mentoring, and guidance to data engineering teams.
9. Stay updated with emerging data technologies and recommend adoption where relevant.