Data Engineer - AI and Data Science Engineer II

Data Engineer

Deloitte Consulting Products (USI)

About the Role

Are you an experienced Data Engineer who has led the development of world-class software or digital products? Are you looking for an opportunity to expand your scope and lead products used by some of the biggest and most influential businesses around the world? If the answer to these questions is yes, we would like to talk with you.

ConvergeCONSUMER™ is a product-driven business that combines differentiated consumer insights with robust prediction and optimization capabilities to help consumer-focused businesses improve decision-making and deliver personalized experiences to drive growth, consumer loyalty, and profitability. We operate with the speed and agility of a startup within the world’s largest professional services firm.

We drive value for our clients by optimizing decisions and actions at a level of granularity only made possible with today’s data and technology. ConvergeCONSUMER’s suite of solutions helps consumer-facing businesses prosper in a world being re-shaped by convergence, where the lines between industries, competitors and collaborators, consumers and suppliers, and even human and artificial intelligence have blurred. Our approach for addressing this complexity is simple: we combine Deloitte’s next-generation technology platforms with decades of experience in the consumer sector and a deep understanding of its unique issues and challenges to drive profitability and future growth for our clients.

Key Responsibilities

We are seeking a highly skilled and experienced Data Engineer to join our team. This role requires both technical fluency in data engineering and an analytical mindset capable of assessing data quality and real-world representativeness. The primary focus of this role is to establish expertise on our library of vendor licensed datasets, perform data pulls to extract insights from the datasets, link and join across datasets, assess the datasets and delivered insights for their validity and believability, and enable downstream data users, including account and product teams, to correctly leverage the data according to their project needs. The ideal candidate will have exceptional SQL and Python skills, expertise in Google BigQuery and PostgreSQL, and ability to convey complex data, concepts, and ideas in succinct, clear fashion to various business stakeholders. Experience with BI tools such as Apache Superset is preferred, Data lineage, apache spark, data product hubs.

• Collaborate with data scientists, analysts, and other stakeholders to understand analysis requirements and deliver solutions.
• Perform exploratory analyses to assess new datasets, identify anomalies, and evaluate representativeness of real-world populations or behaviors.
• Partner with external vendors to troubleshoot discrepancies, clarify data definitions, and improve feed quality.
• Ensure compliance with internal governance standards and data-sharing agreements.
• Serve as a subject matter expert on external datasets, helping teams interpret and leverage them effectively for analysis and product development.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
• Use version control tools like GitHub to manage code changes and collaborate with the team.

Reporting Relationships

Reports to the Engineering Tech Lead / AVP – Product Engineering / AVP – Data Science and works as a core member of the product team alongside Product Management and UX. Partners closely with US-based product owners and portfolio leaders to translate client needs into scalable technical solutions, while collaborating with pFDE, GTM, account, and Deloitte Consulting teams across India and the US.

Qualifications

Required
• 5 to 8 years of relevant experience or equivalent
• Collaborate with data scientists, analysts, and other stakeholders to understand analysis requirements and deliver solutions.
• Perform exploratory analyses to assess new datasets, identify anomalies, and evaluate representativeness of real-world populations or behaviors.
• Partner with external vendors to troubleshoot discrepancies, clarify data definitions, and improve feed quality.
• Ensure compliance with internal governance standards and data-sharing agreements.
• Serve as a subject matter expert on external datasets, helping teams interpret and leverage them effectively for analysis and product development.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
• Use version control tools like GitHub to manage code changes and collaborate with the team.
• GCP architect and big query
• Advanced user of both SQL and Python coding languages with experience in analyzing large data sets

Preferred
• Advanced degree in a related field.
• Experience with BI tools such as Apache Superset.
• Familiarity with cloud environments and deployment patterns.
• Knowledge of data engineering best practices and methodologies.
• Knowledge of feature engineering and practical experience working with data scientists on enabling production feature engineering pipelines at scale.
• Familiar with Apache ecosystem such as Flink, Kafka etc...
• Previous experience in a similar role within a fast-paced development environment.

Core Competencies
• Data Quality & Governance Ownership
• Cross-Functional Collaboration with Data Scientists, Analysts, and External Vendors
• Vendor & External Dataset Management
• Technical Depth in SQL, Python, and Cloud Data Warehousing (GCP/BigQuery)
• Clear Communication of Complex Data to Business Stakeholders

Why This Role Matters

Great products are built by engineers who stay close to the user and take pride in the craft. This role builds a product for the US market from the ground up in India—turning real client problems into scalable product experiences, owning solutions from architecture through production, and iterating based on how clients actually use them. It’s where strong product engineers do their best hands-on work and grow into technical leaders who shape products and platforms next.