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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Management Lead - **Company:** Deloitte T.T.L. - **Location:** Dallas, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Data Architecture, Data Cleansing, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Masking, Data Retrieval, Data Systems, Relational Databases, Fault Tolerance, Information Lifecycle Management, Meta-Data Management, PCI Data Security Standards, Scrum Methodology, Cloud Services, System Testing, Talend, Technical Data Management Systems, Transaction Data, User-Centered Design, Enterprise Data Management, Cloud Platform System, Data Ingestion, Sql Optimization, Informatica Powercenter, Snowflake, Generative AI, Data Strategy, Information Technology, Data Lineage, Collibra, Data Management, Azure Synapse Analytics, Data Pipelines, Amazon Redshift, Databricks - **Published:** August 14, 2026 - **Apply:** https://dejobs.org/x/x/46919AC518364555B81B13E3C653FAE8/job/ ## About the Role * Meticulous attention to detail and quality of work product * Ability to build and sustain professional relationships * Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment * Strong interpersonal skills and professional demeanor * Ability to meet deadlines * Ability to provide clear guidance to others * Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management * Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes The Team, Required * 6yrs+ of dedicated experience in data management, data engineering, or data governance, including proven experience leading cross-functional data initiatives or technical teams in a client-facing or consulting capacity. * Hands-on experience with enterprise data cataloging, MDM, and data quality tools (e.g., Informatica, Talend, Collibra, Profisee, or similar platforms) * Proven expertise in governing and managing Big Data ecosystems, with mandatory experience handling high-volume, high-frequency transactional data sets typical of large enterprise operations. * Deep technical understanding of data ingestion patterns, robust ETL/ELT pipeline design, and data lineage mapping to guarantee highly reliable data availability from source origin to target destination. * Deep proficiency in advanced SQL and relational database architecture, with a strong understanding of data modeling techniques (e.g., Kimball, Inmon) and modern data stack technologies. * Demonstrated ability to lead without direct authority, build consensus on data definitions, and translate highly technical pipeline and architecture concepts for non-technical executive client stakeholders. * Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a business discipline (such as Business Management, Finance, or Economics/Economic Consulting), or equivalent professional experience. * Limited immigration sponsorship may be available * Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve Preferred * FSI Industry Experience: Experience delivering high-volume data solutions exclusively within the Financial Services and Insurance (FSI) sectors (e.g., Retail or Commercial Banking, Property & Casualty Insurance, Wealth Management, Capital Markets, or FinTech). * Secure Delivery Focus: Proven track record of managing data programs that handle highly sensitive data (PII/NPI), incorporating rigorous security reviews, robust data masking/encryption standards, and compliance audits (e.g., PCI-DSS, GLBA, SOX) into the data lifecycle. * Cloud Ecosystems: Advanced experience working within major cloud ecosystems (Microsoft Azure, AWS, or GCP) and cloud-native data warehousing solutions (e.g., Snowflake, Databricks). * Transformation & Automation Experience: Hands-on experience leading digital transformation initiatives, specifically deploying AI/Generative AI (GenAI) and Robotic Process Automation (RPA) to systematically reduce operational redundancy and manual task labor. This includes establishing rigorous system validation protocols and comprehensive risk management frameworks to ensure automated solutions remain secure, accurate, and fully compliant with regulations. * Professional Certifications: Active certifications such as Project Management Professional (PMP), Certified ScrumMaster (CSM), PMI Agile Certified Practitioner (PMI-ACP), or relevant Cloud Practitioner certifications. ## Description Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Data Management Lead you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. If so, consider an opportunity with Deloitte under our Project Delivery Talent Model. Project Delivery Model (PDM) is a talent model that is tailored specifically for long-term, onsite client service delivery., As a Data Management Lead, you will oversee enterprise data management governance/quality, master data management (MDM), and cataloging standards. In this role, you will serve as the strategic steward of enterprise data assets for clients, ensuring high data quality, robust governance, and seamless accessibility across their organizations. In this critical client-facing leadership role, you will bridge the gap between technical data engineering teams and client business stakeholders to design and enforce Master Data Management (MDM) frameworks, data catalogs, and data lifecycle policies. You will drive initiatives that transform raw, high-volume transactional data into secure, reliable, and actionable assets, enabling advanced analytics and supporting clients' enterprise-level strategic objectives. * Pipeline Design & Source-to-Target Availability: Oversee the end-to-end design, governance, and integrity of complex ETL/ELT data ingestion pipelines. Ensure seamless, fault-tolerant data availability and transparent data lineage from disparate source systems to target analytical repositories (e.g., Snowflake, Azure Synapse, AWS Redshift). * Lead the data management strategy for high-volume, high-velocity transactional data. Ensure that client data architectures are optimized for massive scale, rapid data retrieval, and operational resilience. * Establish, enforce, and scale enterprise data governance frameworks, policies, and standard operating procedures to ensure data accuracy, consistency, and regulatory compliance within client environments. * Lead the design and implementation of MDM solutions and data cataloging tools (e.g., Collibra, Alation, Informatica) to help clients maintain a single, trusted source of truth across complex enterprise ecosystems. * Architect and deploy automated data quality monitoring workflows; define critical data elements (CDEs), track metadata, and establish KPIs to proactively identify and remediate data anomalies before they impact downstream availability * Mentor data engineers and analysts while partnering tightly with client stakeholders (product, finance, and operations) to translate their specific business requirements into scalable, robust data architectures. * Lead data management initiatives within an Agile framework, managing sprint backlogs, capacity planning, and project delivery timelines on behalf of clients. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers)