Deloitte Recruitment Program 2025 | Hiring Data Engineer – Senior Analyst

Qualifications

Education:

• Bachelor’s degree in Computer Science or Business Information Systems or MCA or equivalent degree.

Skills Required:

• 2 to 5 years Advanced Level of experience in Azure Data engineering
• Expertise in Development, deployment and monitoring ADF pipelines (using visual studio and browsers)
• Expertise in Azure databricks internal programming using (PySpark, SparkR and SparkSQL) or Amazon EMR (Elastic MapReduce).
• Expertise in managing azure storage (Azure Datalake Gen2, Azure Blob Storage, Azure SQL database) or Azure Blob Storage, Azure Data Lake Storage, Azure Synapse Analytics, Azure Data Factory
• Advanced programming skills in Python, R and SQL (SQL for HANA, MS SQL)
• Hands on experience in Visualization tools (Tableau / PowerBI)
• Hands on experience in Data science studios like (Dataiku, Azure ML studio, Amazon SageMaker)

Job Description & Responsibilities:

The Data Engineer is an integral part of the technical application development team and primarily responsible for analyze, plan, design, develop, and implement the Azure Data engineering solutions to meet strategic, usability, performance, reliability, control, and security requirements of Data science processes. Requires demonstrable knowledge in areas of Data engineering, AI/ML, Data warehouse and reporting applications. Must be innovative.

Work you will do:

A unique opportunity to be a part of growing team that works on a premier unified data science analytics platform within Deloitte. You will be responsible for implementing/delivering/supporting Data engineering and AI/ML solutions to support the Deloitte US Member Firm.

Outcome-Driven Accountability

• Collaborate with business and IT leaders to develop and refine ideas for integrating predictive and prescriptive analytics within business processes, ensuring measurable customer and business outcomes.
• Decompose complex business problems into manageable components, facilitating the use of multiple analytic modeling methods for holistic and valuable solutions.
• Develop and refine prototypes and proofs of concepts, presenting results to business and IT leaders, and demonstrating the impact on customer needs and business outcomes.

Technical Leadership and Advocacy

• Engage in data analysis, generating and testing hypotheses, preparing and analyzing historical data, identifying patterns, and applying statistical methods to formulate solutions that deliver high-quality outcomes.
• Develop project plans, including resource needs and task dependencies, to meet project deliverables with a focus on incremental and iterative delivery.

Engineering Craftsmanship

• Participate in defining project scope, objectives, and quality controls for new projects, ensuring alignment with customer-centric engineering principles.
• Present and communicate project deliverable results, emphasizing the value delivered to customers and the business.

Customer-Centric Engineering

• Assist in recruiting and mentoring team members, fostering a culture of engineering craftsmanship and continuous learning.

Incremental and Iterative Delivery

• Stay abreast of changes in technology, leading new technology evaluations for predictive and statistical analytics, and advocating for innovative, lean, and feasible solutions.