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. In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.
At PwC - AC, we are looking for an Azure Senior Manager- Data & AI who will have:
Passion for technology, in the space of Analytics
Hands-on experience in Cloud Analytics, Data Engineering
Hands on experience in building large data repositories in Cloud
Hands on experience in designing and implementing large scale transformation programs in Cloud, Enterprise Data Management
Drive the design, development, and deployment of data pipelines and analytics platforms using Azure Data Services and Microsoft Fabric
Architect and oversee PySpark Notebooks and SparkSQL jobs to process large-scale datasets efficiently
Develop and optimize SQL database solutions to support analytics, reporting, and data integration needs
Engage with business stakeholders, to understand client requirements and build technical solutions and delivery plans
Business / domain knowledge along with technical expertise
Experience in working with cross functional and geographically separated teams
Experience in technical scoping of projects, drawing delivery plans
Experience in leading technical teams, guiding and mentoring team members
Experience in presenting technical and business executive presentations to leadership
Responsible for the design and execution of abstractions and integration patterns (APIs) to solve complex distributed computing problems
Years of Experience: Candidates with 12-16 years of hands on experience
Position Requirements
Must Have:
Proficient with Azure cloud computing, including big data technologies.
Experience with deep understanding in both traditional and modern data architecture and processing concepts including relational databases (e.g., SQL Server, MySQL, PostgreSQL), Data warehousing, big data, NoSQL and business analytics
Rich experience working in Azure ADLS, Data Bricks, Data Flows, HDInsight, Azure Analysis services
Experience in building stream-processing systems, using solutions such as Storm or Spark-Streaming
Understanding of big data use-cases and Lambda/Kappa design patterns
Hands-on experience with Microsoft Fabric and its components
Proficient in PySpark Notebooks for building scalable data processing pipelines
Strong command over SQL databases and performance tuning for analytical workloads
Solid experience with SparkSQL for complex data transformations and querying
Knowledge of real time/stream analytics trends.
Architecture, design, implementation, and/or support of complex application architectures (i.e. having an architectural sense for connecting data sources, data visualization, structured and unstructured data, etc.)
Demonstrable hands on experience implementing Big Data solutions using Microsoft Data Platform and Azure Data Services
Azure SQL DB, Azure Synapse Analytics, Azure HD Insight, Azure Data Lake Storage, Azure Data Lake Analytics, Azure Machine Learning, Stream Analytics, Azure Data Factory, Azure CosmosDB and Power BI
Exposure to Open Source technologies such as Apache Spark, Hadoop, NoSQL, Kafka, Solr/Elastic Search
Should be well versed with quality processes and implementation
Excellent communication skills
Business / domain knowledge in one of the domains -Financial Services/ Healthcare/ Consumer Market/Industrial Products/ Telecommunication,Media and Technology /Deal advisory along with technical expertise
Good knowledge of Application DevOps tools (Git, CI/CD Frameworks) - Experience in Jenkins or Gitlab with rich experience in source code management like Code Pipeline, Code Build and Code Commit
Good understanding of Data Modeling and Data Architecture
Good To Have Skills
Knowledge of Snowflake Cortex, Snowflake AI features and Sigma.
Knowledge of data integration tools like Informatica, DataStage, or Ab Initio.
Familiarity with data visualization tools such as Tableau or Qlik.
Experience with programming languages such as Python, Java, or PySpark.
Certifications related to cloud data warehousing or Snowflake.
Experience in pre-sales engagements and proposal development.
Data Modeling and Data Architecture
Cloud - AWS, GCP, Oracle-Cloud
Business Intelligence - MicroStrategy, Business Objects, Cognos
Data Appliance - Teradata, Netezza
Additional Skills
Excellent communication skills, client presence, presentation skills
People skills, Leadership skills
Engage with business and technical teams to drive consensus
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