Data Engineering Consultant

Deloitte provides Technology & Transformation services to nearly 90% of the Fortune Global 500® and thousands of private companies. Technology & Transformation services cover world class and innovative technology development & implementation and architecture design & technology strategy. Deloitte also has Audit & Assurance, Strategy, Risk & Transactions and Tax & Legal services.

Deloitte’s technology strategy and transformation specialists excel at smoothing your path. We help organisations develop the strategies and implement the systems that build business value and drive performance. From system replacement to IT transformation and implementing more efficient development processes, our professionals bring deep knowledge and experience to your most complex challenges.

Deloitte’s Technology Strategy, Vision & Architecture offerings provide the vision, strategy and roadmap for wide-scale transformations to your IT infrastructure and operations, aligning the technological changes with business goals. We work with senior leadership to set the technology direction, help you to define your target state—including desired components such as cloud services and on-premises functions—and prepare the plans for the transformation.

We’ll guide you through new high-level enterprise architecture as well as architectures for applications, data and infrastructure. And we’ll help you to select your technology vendors, providing guidance on complex Issue such as the interaction between Solutions components to work toward a successful outcome and deliver performance, security and scalability.

The Deloitte approach to Business of Technology Transformation will help your organisation drive increased value from your day-to-day technology operations. Our teams support your IT ecosystem in areas such as cost reduction, design, governance, benchmarking performance and selecting and managing outsourced solutions.

We are seeking high-potential candidates to join our Technology & Transformation - Engineering, AI & Data team.

Be part of work that delivers meaningful impact — for businesses, people and the world.

Join us.

What you'll do:

As a Data Engineering Consultant, you will:

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or equivalent experience,
• 2 to 5 years of experience in data engineering,
• Strong experience with SQL and relational databases (PostgreSQL, SQL Server, MySQL, Oracle),
• Proficiency in at least one programming language: Python, Scala, or Java,
• Experience with cloud platforms (AWS, GCP, or Azure) and cloud-native data services,
• Knowledge of data warehousing concepts and modern analytics architectures (Lakehouse, DWH),
• Experience with orchestration tools (Airflow, Azure Data Factory, or similar),
• Experience with data integration and ETL/ELT processes,
• Experience with big data technologies (Hadoop, Spark, Kafka),
• Familiarity with CI/CD practices and version control systems (Git),
• Understanding of data quality, data governance, and security best practices,
• Experience working with structured and semi-structured data (JSON, Parquet, Avro),
• Ability to optimize data pipelines for performance, scalability, and reliability,
• Demonstrated ability to integrate Generative AI tools (e.g., GitHub Copilot, ChatGPT, LLMs) into daily development workflows to enhance coding efficiency, automate documentation, and streamline troubleshooting,
• Excellent communication and interpersonal skills,
• Strong problem-solving and analytical skills,
• Experience with Agile (Scrum, Kanban, Lean) methods,
• Certifications in relevant data technologies,
• Fluent in English (written and spoken).

Nice-to-Have: Generative AI Development Experience

We highly value candidates who have technical experience in developing and deploying Generative AI solutions. Key competencies for this area include:

• LLM Orchestration: Hands-on experience with frameworks such as LangChain or LlamaIndex.
• RAG Architecture: Solid understanding of Retrieval-Augmented Generation (RAG) patterns for connecting LLMs to private data sources.
• Vector Databases: Experience with vector storage and indexing tools like Pinecone, Weaviate, Chroma, or Milvus.
• Model Integration: Ability to work with LLM APIs (OpenAI, Anthropic, Azure OpenAI) and open-source models (Llama, Mistral).
• Prompt Engineering: Technical proficiency in designing and optimizing prompts for complex data tasks.

Challenges

• Managing the complexity of growing data volumes and variety,
• Ensuring data quality and consistency across multiple sources,
• Optimizing data processing and storage costs,
• Balancing the need for agility with data governance and compliance requirements,
• Solid business acumen, ability to bridge business and tech sides,
• The potential candidate needs excellent business and communication skills to work with business owners to develop and define key business questions, support analysis, improvement, and creation of metrics and dashboards for the learning organization,
• Working with international teams for global projects.

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