Big Data Architect
The big data solutions architect is responsible for leading the strategy formulation and architectural design of the enterprise data lake framework and analytical tools initiatives. This role requires collaborating with executive-level business and technology leaders as well as big data platform, data lake, cloud, DevOps, security and infrastructure engineers and architects across business, functional and geographic boundaries. A passionate big data solutions architect who can leverage their technical expertise to work on disruptive technologies, enable new business ideas and solve big data architecture and engineering problems. Work for the enterprise data architecture team and enterprise big data platform and data analytics engineering team. Provides architectural and engineering leadership and direction to the team(s) of significant scope/impact (employees, contract personnel and vendor partners) dedicated to portfolio(s) of technical business applications. Define, develop, govern and adhere to the architecture principles and development standards set by the team to deliver high-quality solutions that will run across multiple environments with high performance. Responsibilities
• Strategy Development - Develop current to future state architecture road maps. Align and promote enterprise technology (data, infrastructure, application and security) principles and strategy. Contribute to and author application and capability strategies. Establish, maintain and apply architecture standards, disciplines and principles.
• Design - Use appropriate design techniques and methodologies to translate project requirements into detailed designs, consistent with platform strategy and road map. Design external system interface architecture that includes appropriate application of techniques and standards. Determine integrated hardware and software architecture solutions that meet performance, usability, scalability, reliability, security and business/functional requirements. Diligently teaming with the cloud engineering, delivery, infrastructure (storage and compute), network, security teams to deliver an optimal big data solutions and experience for the enterprise.
• Risk Assessment - Create effective and efficient control patterns, conduct risk evaluations and enforce policies and standards to enable the enterprise to conduct business at an appropriate level of risk. Ensure capabilities are reviewed and compliant with appropriate levels of risk respective to hardware/software currency, performance/availability, security and information/transaction integrity and drive the awareness of required improvements.
• Practice leadership - Maintain deep expertise in architectural modeling, frameworks, emerging technologies and best practices. Mentor and develop less experienced technical staff. Provide technical leadership in both business-as-usual and crisis conditions. Recommend new procedures and processes to drive desired results on diverse projects. Perform industry research with external parties and maintain networks amongst peers.
• Governance - Develop and communicate governance parameters that take into account stakeholder's interests and processes with measurable results. Partner with other architects to ensure alignment and integration across portfolio boundaries and promote an enterprise focus on big data and analytics solutions. Develop and build strong relationships within and across the lines of business and use effective communication skills to influence and accomplish strategic application architecture objectives.
• Research - Provide thought leadership with respect to R&D of the latest and greatest big data and advanced analytics toolsets and data lake engineering practices, and perform comparative analysis of the methodologies and toolsets to propose the best fit. Research and recommend technology to improve current systems. Define and lead Proof-of-Concept work (PoCs) for advanced analytics toolsets - through defining PoC objectives and requirements, presenting the proposals in senior leadership forums and architecture boards, reviewing PoC results, and authoring reference architectures for enterprise usage.
• Provide guidance for devising data lakes and advanced analytic tool best practices, processes, technology & solution patterns with respect to data discovery, preparation, model training, model scoring, risk, audits, machine learning flows, basic and advanced analytics tool integration and guide other enterprise teams in adopting data lake engineering, platform and tools best practices and reference architecture patterns.
• Act as a strong proponent for promoting open source technology culture within the organization. Provides thought leadership with respect to the R&D of the open source analytical toolset and big data technologies.
• Work closely with various stakeholders in US team with a collaborative approach. Required Qualifications
• Liaison as an intermediary between data scientists, data lake engineers and platform administrators to understand the requirements, provide technical guidance/mentorship and consultation towards resolution of their queries.
• Understand the data science, advanced analytics, and machine learning roadmaps and build tool strategies, road maps and reference architectures to support the organization's data-driven strategy. Partner with data analysts and data scientists to propose advance analytics technology solutions that meet the business needs and align to the enterprise roadmap.
• Lead technical discussions across infrastructure teams on tool and infrastructure performance parameters such as CPU, disk IO, memory usage, disk space etc. in order to provide an optimal performance experience to the end users.
• Masters or bachelor's degree in computer science engineering or related technical field.
• 8 - 13 years of broad experience across architecture practices (data, infrastructure, applications and security) with depth of experience in at least one area.
• Knowledge of Enterprise-wide architecture and ability to 'see the big picture' and how it affects current and future technologies.
• Internal/External consulting experience that spans organizational boundaries and includes influencing technology & business leaders.
• Depth of experience in the architecture, design, implementation and support of complex enterprise solutions.
• Exposure to multiple, diverse technical configurations, technologies and process improvements.
• Good hands-on past experience as a developer and programmer in developing modules requiring complex logic and integrations.
• AWS experience:
o Worked with or have sound knowledge of AWS cloud services in the areas of big data, data lakes, analytics, machine learning, storage, compute, network and security. (required)
o AWS Solution Architect - Associate and/or AWS Big Data - Specialty certifications (strongly preferred)
• Data Science experience (strongly preferred):
o Experience of working in data science domain and developing models.
o Well versed with AI and machine learning fundamentals
o Experience with industry advanced analytic and machine learning tools, but commercial and open source (e.g. Amazon SageMaker, Dataiku, Data Robot, SAS Viya, R, etc.)
o Experience with business intelligence and analytics tools such as Power BI, Tableau, and Amazon QuickSight.
• Sound fundamentals of big data concepts such as data ingestion frameworks, distributed data systems and processing, optimizing data lake storage, streaming solutions, data APIs.
• Sound fundamentals of database concepts and experience with relational or non-relational database types such as document, key-value, graph, etc.
• Experienced in driving initiatives working closely with the leadership and stakeholders.
• Ability to quickly perform critical analysis and use creative approaches for solving complex problems.
• Strong academic background.
• Excellent written and verbal communication skills and strong relationship building skills.