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Line of Service
AdvisoryIndustry/Sector
Not ApplicableSpecialism
Data, Analytics & AIManagement Level
ManagerJob Description & Summary
At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.*Why PWC
At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. "
Responsibilities:
Deep expertise
Databricks: PySpark/SQL, Delta Lake, Structured Streaming, Jobs/Workflows, Unity Catalog, cluster policies, performance tuning.
Azure: ADLS Gen2, Event Hubs/Kafka, Azure Functions/Logic Apps, Key Vault, ADF, Synapse; VNETs, Private Endpoints, Managed Identity.
Fabric: Lakehouse, OneLake, Pipelines, Dataflows Gen2, Shortcuts, semantic models, governance integration with Purview and Power BI.
Architecture patterns
Lakehouse, medallion, Data Mesh/data products, CDC with Debezium/Fivetran/ADF mapping data flows, SCD handling, schema evolution.
Batch and streaming design, watermarking, state store management, idempotency, backfills, and late/duplicate data handling.
Data management
Dimensional and semantic modeling, Data Vault/Kimball, query performance, partitioning, Z-Order, OPTIMIZE/VACUUM, file sizing.
DQ frameworks (Great Expectations/Deequ), monitoring/observability (Log Analytics, Databricks metrics), SLA/SLO design.
Security and compliance
Purview lineage and classification, Unity Catalog governance, PII/PHI handling, encryption, tokenization; audit, SOC2/ISO, GDPR/DPDP familiarity.
Mandatory skill sets:
Azure Data Architect
Preferred skill sets:
Azure Data Architect
Years of experience required:
7-12 Years
Education qualification:
B. Tech/MBA/MCA / M. Tech
Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Bachelor of EngineeringDegrees/Field of Study preferred:Certifications (if blank, certifications not specified)
Required Skills
Generative AIOptional Skills
Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Coaching and Feedback, Communication, Creativity, Data Anonymization, Data Architecture Development, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling {+ 32 more}Desired Languages (If blank, desired languages not specified)
Travel Requirements
Available for Work Visa Sponsorship?
Government Clearance Required?
Job Posting End Date
April 12, 2026Auto-Apply to Data Architect Jobs with your AI JobCopilot
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