Data Engineering Lead Architect - Azure
$145k - $190kFractal
Job Description
Data Engineering Lead Architect – Azure
\n \nFractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner.
\n \nPlease visit Fractal | Intelligence for Imagination for more information about Fractal.
\n \nNote: This position is not eligible for Immigration Sponsorship at this time.
\n \nLocation: New York City, NY
\n \nPosition Overview:
\nIf you are an extraordinary architect who loves pushing boundaries to solve complex business problems through creative, scalable solutions, we would like to speak with you. As a Data Engineering Lead Architect - Azure, you will join our Technology team and help deliver enterprise-scale data engineering platforms and data products for Fortune clients worldwide.
\n \nIn this highly visible leadership role, you will define data strategy, architecture standards, and governance frameworks while driving the delivery of secure, resilient, and business-ready data products on Microsoft Azure and Microsoft Fabric. You will lead complex programs from architecture through release, partner with senior business and technology stakeholders, and mentor engineering teams to build reusable capabilities that accelerate data and analytics transformation.
\n \nJob Responsibilities:
\nArchitecture & Data Product Strategy
\n- \n
- Design and build cloud-native data platforms and data products on Microsoft Azure, selecting the services, tools, architecture patterns, and engineering methodologies best suited to each client’s needs. \n
- Define enterprise data architecture standards, reference architectures, design patterns, guiding principles, and platform blueprints for scalable, reusable, secure, and governed data products. \n
- Architect and deliver data products on Microsoft Fabric, using enterprise master data and SAP product hierarchies as foundational data assets. \n
- Translate business requirements into technology specifications, target-state architectures, data models, delivery plans, release strategies, and operational roadmaps. \n
Technical Delivery & Engineering Excellence
\n- \n
- Lead technical programs end to end, from discovery and solution design through build, testing, release, and production support, with ownership of the complete delivery lifecycle. \n
- Develop scalable software, reusable frameworks, and engineering practices required for the end-to-end execution of large data programs. \n
- Apply software engineering principles across all phases of the SDLC to build resilient, observable, maintainable, and high-performing solutions. \n
- Guide the implementation of batch, streaming, lakehouse, warehouse, and real-time data processing solutions across the Azure ecosystem. \n
- Establish and advance CI/CD, DevOps, Infrastructure as Code, containerization, release management, and automated testing practices. \n
Data Governance, Quality & Trust
\n- \n
- Drive enterprise data governance initiatives and partner with business stakeholders to establish clear ownership, accountability, stewardship, and decision rights across functions. \n
- Establish and enforce data quality frameworks, controls, validation rules, observability, lineage, monitoring standards, and certification processes that produce trusted, business-ready data. \n
- Lead the development and certification of data products aligned with organizational quality, governance, business validation, and compliance requirements. \n
- Promote effective metadata management, master data management, cataloging, and lifecycle governance across the data platform. \n
Client Leadership & Team Development
\n- \n
- Partner with senior business and technology leaders to align data architecture decisions with measurable business outcomes and enterprise priorities. \n
- Be an integral part of large-scale client business development, solutioning, estimation, proposal, and delivery engagements. \n
- Mentor architects and engineering teams, provide hands-on technical direction, and ensure adherence to architecture standards and engineering best practices. \n
- Collaborate with global consulting teams across multiple projects, workstreams, and geographies. \n
- Build the knowledge base, reusable assets, and delivery playbooks required to execute increasingly complex data and analytics transformation programs. \n
Minimum Qualifications:
\n- \n
- 10-15 years of technology experience, including significant leadership experience in enterprise data architecture, data engineering, data platforms, data warehousing, or analytics transformation programs. \n
- Extensive experience designing and implementing cloud-native data solutions on Microsoft Azure. \n
- Hands-on expertise with Microsoft Fabric, including Lakehouse architecture, OneLake, Data Factory, Data Engineering, Data Warehousing, and Real-Time Analytics capabilities. \n
- Proven success defining enterprise architecture standards, reference architectures, design patterns, and data platform blueprints. \n
- Strong command of enterprise data governance, metadata management, master data management, data cataloging, data stewardship, and data product operating models. \n
- Expertise in data quality management, data validation frameworks, observability, lineage, monitoring, and data product certification. \n
- Experience integrating SAP master data, product hierarchies, and enterprise systems into modern cloud data platforms. \n
- Deep experience with Azure data services, including Databricks, Azure Data Lake Storage, Azure Data Factory, Event Hubs or Kafka, Synapse Analytics, Cosmos DB, and related platform services. \n
- Strong proficiency in SQL and experience with relational and NoSQL technologies such as PostgreSQL, MongoDB, Cassandra, and MySQL. \n
- Hands-on experience with distributed processing and streaming technologies, including Spark and Kafka. \n
- Expertise in Python, Spark, data modeling, and modern data engineering frameworks. \n
- Strong experience with CI/CD, DevOps, Infrastructure as Code, Docker, and Kubernetes. \n
- Excellent stakeholder management, consulting, communication, and presentation skills, with the ability to engage senior business and technology leaders. \n
- Ability to lead and collaborate with global consulting teams across multiple projects and geographies. \n
Preferred Qualifications:
\n- \n
- Experience with Microsoft Purview, enterprise data catalogs, metadata management platforms, and Master Data Management solutions. \n
- Knowledge of Data Mesh, domain-oriented data products, event-driven architecture, and real-time analytics patterns. \n
- Experience with Snowflake, SAP Datasphere, SAP BW, or adjacent enterprise data platforms. \n
- Azure or Microsoft Fabric certifications. \n
- Experience in the consumer goods industry or with product, customer, and commercial data domains. \n
- Experience establishing data product certification frameworks and governance processes at enterprise scale. \n
Education & Experience:
\n- \n
- Bachelor’s degree in Computer Science, Engineering, or a related technical field; a master’s degree is preferred. \n
- B.E., B.Tech., M.Tech., or an equivalent combination of education and relevant professional experience. \n
- 10-15 years of relevant technology experience in data architecture, data engineering, cloud platforms, or enterprise analytics transformation. \n
Core Technology & Leadership Skills:
\nMicrosoft Fabric, Azure Data Engineering, Azure Data Factory, Azure Data Lake Storage, Databricks, Enterprise Data Architecture, Data Product Development, SAP Master Data Integration, SAP Product Hierarchies, Data Governance, Data Quality Management, Data Modeling, SQL, Python, Spark, Kafka, CI/CD, DevOps, Docker, Kubernetes, Stakeholder Management, and Solution Architecture.
\n \nPay:
\nThe wage range for this role takes into account the wide range of factors that are considered in making compensation decisions, including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is: $145,000 - $190,000. In addition, you may be eligible for a discretionary bonus for the current performance period.
\n \nBenefits:
\nAs a full-time employee of the company or as an hourly employee working more than 30 hours per week, you will be eligible to participate in the health, dental, vision, life insurance, and disability plans in accordance with the plan documents, which may be amended from time to time. You will be eligible for benefits on the first day of employment with the Company. In addition, you are eligible to participate in the Company 401(k) Plan after 30 days of employment, in accordance with the applicable plan terms. The Company provides for 11 paid holidays and 12 weeks of Parental Leave. We also follow a “free time” PTO policy, allowing you the flexibility to take the time needed for either sick time or vacation.
\n \nFractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
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