Data Engineering Manager / PFDE - Engineering Delivery Manager II

Data Engineering Manager – Product Forward Deployed 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.
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Work with Product Managers/Owners to understand how products can be used and should be implemented to solve client problems.
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Work with Project Managers to understand client requirements and brainstorm on solutions, implement the assets/products as applicable. Perform exploratory data analysis on large datasets (several GB to TB) to define analytical models and convert them into Model Ready Datasets (MRD)
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Collaborate with data scientists, analysts, and other stakeholders to understand analysis requirements and deliver solutions.
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Guide teams to perform exploratory analyses to assess new datasets, identify anomalies, and evaluate representativeness of real-world populations or behaviors across multiple engagements
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Build, test, validate and demonstrate analytical models through various relevant error metrics and calibration techniques. Present the forecasting accuracy results to the client team.
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Partner with external vendors to troubleshoot discrepancies, clarify data definitions, and improve feed quality.
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Ensure compliance with internal governance standards and data-sharing agreements.
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Serve as a subject matter expert on external datasets, helping teams interpret and leverage them effectively for analysis and product development.
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Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
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Use version control tools like GitHub to manage code changes and collaborate with the team
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Support and coach your team on best solutioning practices, development tools, and pathfinding and surveys for technologies
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Set technical direction, coach talent, enforce standards, align product/engineering/ops, and manage engagement risks
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Deploy advanced use of both SQL and Python coding languages in analyzing large data sets
Reporting Relationships
Reports to the AVP – Product Forward Deployed Engineer (pFDE) and works at the intersection of data, product, and client delivery. Partners with US-based product and portfolio leaders to translate client needs into scalable data solutions, leveraging and validating complex datasets to generate actionable insights. Collaborates with Product, GTM, account, and Deloitte Consulting teams across India and the US.
Qualifications
Required
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10-14 years of relevant consulting experience (or equivalent) with a focus on storytelling and building Model Ready Datasets (MRD) based on analysis of large external and client data sets
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Bachelor's degree in Engineering, Computer Science, Data Analytics, Statistics, or a related quantitative field
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Work with Product Managers/Owners to understand how products can be used and should be implemented to solve client problems.
•
Work with Project Managers to understand client requirements and brainstorm on solutions, implement the assets/products as applicable. Perform exploratory data analysis on large datasets (several GB to TB) to define analytical models
•
Collaborate with data scientists, analysts, and other stakeholders to understand analysis requirements and deliver solutions.
•
Guide teams to perform exploratory analyses to assess new datasets, identify anomalies, and evaluate representativeness of real-world populations or behaviors across multiple engagements
•
Build, test, validate and demonstrate analytical models through various relevant error metrics and calibration techniques. Present the forecasting accuracy results to the client team.
•
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
•
Support and coach your team on best solutioning practices, development tools, and pathfinding and surveys for technologies
•
Set technical direction, coach talent, enforce standards, align product/engineering/ops, and manage engagement risks
•
Advanced user of both SQL and Python coding languages with experience in analyzing large data sets
Preferred
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Advanced degree in a related field.
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Experience with BI tools such as Apache Superset.
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Familiarity with cloud environments and deployment patterns.
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Knowledge of data engineering best practices and methodologies.
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Knowledge of feature engineering and practical experience working with data scientists on enabling production feature engineering pipelines at scale.
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Previous experience in a similar role within a fast-paced development environment.
Core Competencies
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Data Quality, EDA, MRD generation & Governance Ownership
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Cross-Functional Collaboration with Product Managers, Data Scientists, and External Vendors
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Vendor & External Dataset Management
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Technical Depth in SQL, Python, and Cloud Data Warehousing (GCP/BigQuery)
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Technical Leadership & Team Coaching
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Clear Communication of Complex Data to Business Stakeholders
Why This Role Matters
Product Forward Deployed Engineers bridge deep product and domain expertise with real client problems. They apply data and AI/ML capabilities to deliver scalable solutions, translate client learnings back into the product, and shape how Converge Consumer turns data into better decisions. It’s a hands-on path to becoming a leader at the intersection of product, data, and client impact.