Job Title:  Technology & Transformation - Engineering - Senior Consultant - Data Engineer (AI Solutions)

The Team

Deloitte’s Technology & Transformation practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning. 

Your work profile:

As a Senior Consultant in our Technology & Transformation Team you’ll build and nurture positive working relationships with teams and clients with the intention to exceed client expectations: -

• Design, develop and deploy solutions using different tools, design principles and conventions.
• Configure robotics processes and objects using core workflow principles in an efficient way; ensure they are easily maintainable and easy to understand.
• Understand existing processes and facilitate change requirements as part of a structured change control process.
• Solve day to day issues arising while running robotics processes and provide timely resolutions.
• Maintain proper documentation for the solutions, test procedures and scenarios during UAT and Production phase.
• Coordinate with process owners and business to understand the as-is process and design the automation process flow.

Key skills required: 

• Design, build, and maintain data pipelines that serve the needs of multiple stakeholders including software developers, data scientists, analysts, and business teams.
• Ensure data pipelines are modular, resilient, and optimized for performance and low maintenance.
• Collaborate with AI/ML teams to support training, inference, and monitoring needs through structured data delivery.
• Implement ETL/ELT workflows for structured, semi-structured, and unstructured data using cloud-native tools.
• Work with large-scale data lakes, streaming platforms, and batch processing systems to ingest and transform data.
• Establish robust data validation, logging, and monitoring strategies to maintain data quality and lineage.
• Optimize data infrastructure for scalability, cost-efficiency, and observability in cloud-based environments.
• Ensure compliance with governance policies and data access controls across projects.

Required Qualifications:

• Bachelor’s degree in computer science, Information Systems, or a related field.
• 4+ years of experience designing and deploying scalable data pipelines in cloud environments.
• Proficiency in Python, SQL, and data manipulation tools and frameworks (e.g., Apache Airflow, Spark, dbt, Pandas).
• Practical experience with data lakes, data warehouses (e.g., Redshift, Snowflake, BigQuery), and streaming platforms (e.g., Kafka, Kinesis).
• Strong understanding of data modelling, schema design, and data transformation patterns.
• Experience working with Azure (Data Factory, AzureML Studio, Azure Storage).
• Proven experience in handling Semi and Unstructured data.
• Familiarity with CI/CD for data pipelines and infrastructure-as-code (e.g., Terraform,
• CloudFormation).

Preferred Qualifications:

• Exposure to building data solutions that serve AI/ML pipelines, including feature stores and real-time data ingestion.
• Familiarity with observability, data versioning, and pipeline testing tools.
• Experience engaging with diverse stakeholders, gathering data requirements, and supporting iterative development cycles.
• Background or familiarity with the Power, Energy, or Electrification sector is a strong plus.
• Knowledge of security best practices and data compliance policies for enterprise-grade systems.