BIG DATA SOLUTION ARCHITECT JOB DESCRIPTION

Every IT consulting firm that promises data transformation to its clients eventually has to deliver one. That delivery depends on someone who can translate a client's fragmented data estate into a coherent, cloud-native architecture - and then own the technical roadmap from pre-sales through go-live. The Big Data Solution Architect holds that accountability, working across distributed Hadoop and cloud platforms while engaging C-level stakeholders on ROI and architecture reviews. No other role in the practice owns both the solution design and the client relationship through implementation.

As the Big Data Solution Architect, you design and deliver scalable enterprise data solutions for clients across industries, owning technical architecture decisions from initial proposal through production deployment. You operate as a senior practitioner within a consulting practice, partnering with business development, implementation engineers, and client executives to ensure solutions meet both technical and commercial requirements.

Career Impact: Consistent delivery of cloud data architecture engagements - spanning Data Warehouses, Data Lakes, and real-time pipelines - builds the kind of portfolio that distinguishes a senior architect in the enterprise consulting market.

Business Impact: The architectures produced in this role directly determine whether client organizations can operationalize their data assets at scale, with measurable ROI presented to executive stakeholders.

Growth Opportunity: Exposure to pre-sales, ROI modeling, and C-level advisory expands your scope toward a Principal Architect or practice leadership track within the consulting firm.

• Design scalable big data architecture proposals covering data acquisition, storage, transformation, and distribution for enterprise clients.
• Architect and implement cloud-based data solutions spanning Data Warehouses, Data Lakes, and real-time streaming pipelines.
• Lead client engagements from requirement definition and pre-sales through solution go-live and post-deployment review.
• Conduct solution architecture audits of existing client environments and present ROI-backed recommendations to senior stakeholders.
• Develop technical roadmaps for data science initiatives including predictive modeling and machine learning integration.
• Define data management standards, policies, and best practices for client implementation teams.
• Mentor junior consultants and IT architects within the practice on architecture patterns and delivery methodology.
• Produce architecture documents, executive presentations, and technical position papers to communicate solutions to client and internal teams.

• Bachelor's degree in Information Technology, Computer Science, Statistics, or equivalent work experience.
• 8 or more years of experience in big data architecture and enterprise data solution delivery, with demonstrated client-facing consulting experience.
• Demonstrated ability to design distributed data processing systems across on-premises and cloud environments.
• Proven expertise in data modeling and database design covering Data Warehousing, Business Intelligence systems, and MPP platforms.
• Strong command of ETL and ELT transformation strategies, Lambda architecture, and schema-on-read and schema-on-write patterns.
• Experience leading architecture reviews, calculating ROI, and presenting technical recommendations to C-level audiences.
• Strong communication skills for coordinating cross-functional teams including developers, architects, and external technology partners.
• Ability to assess competing priorities and define critical-path decisions under time and budget constraints.

• Experience working in highly regulated client environments such as Banking, Telecom, or similarly compliance-driven sectors.
• Proven track record leading pre-sales activities including technical proposal development and solution scoping for enterprise data projects.
• Familiarity with container orchestration and resource management in production data environments.
• Recognized cloud certification in at least one major provider, such as the Azure Data Engineer Associate credential.

• Architecture proposals advanced to signed engagements, as a share of pre-sales opportunities supported.
• Time from requirements sign-off to solution go-live, measured in weeks against project plan.
• ROI realization rate on delivered architectures, validated against client-reported business outcomes.
• Audit findings resolved per engagement, reflecting the depth and accuracy of architecture review work.
• Client satisfaction score on technical delivery, collected at project close by the consulting practice.
• Typical tools: Distributed processing frameworks (commonly Spark and Hadoop ecosystem); cloud data platforms (commonly AWS, Azure GCP native services); orchestration and pipeline tools (commonly Kafka and Databricks).

• Base Salary Range: $145,000 to $185,000 annually, depending on seniority and location.
• Bonus: Performance-based, typically 10 to 15 percent of base salary.
• Equity: Varies by firm; RSUs or profit-sharing offered at select consulting organizations.
• Health Benefits: Medical, dental, and vision coverage for employee and dependents.
• PTO: 15 to 20 days annually, plus standard US federal holidays.
• Common Perks: Certification reimbursement, conference attendance budget, and remote or hybrid flexibility for non-client-site weeks.

Figures are estimates based on general US market benchmarks and may be outdated. Adjust based on location, company size, and seniority level.

Work authorization in the United States is required for all applicants. All qualified candidates will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, veteran status, or any other characteristic protected under applicable federal, state, or local law. Reasonable accommodations are available to individuals with disabilities throughout the application and employment process upon request. Final offers of employment are contingent on successful completion of a background check consistent with applicable law.

The Big Data Solution Architect owns the design and deployment of scalable big data infrastructure on Hadoop, partnering with Engineering teams to define data acquisition, transformation, and machine learning roadmaps. Working across client-facing and internal initiatives, this role delivers architecture audits, performance test strategies using tools such as LoadRunner and JMeter, and technical documentation that enables stable, high-performance data systems.

Key Responsibilities

• Develop proposals for implementation and design of scalable big data architecture.
• Participate in customer workshops and present proposed solutions.
• Design, implement, and deploy high-performance custom applications at scale on Hadoop.
• Define and develop network infrastructure solutions to enable partners and clients to scale NoSQL and relational database architecture.
• Define common business and development processes, platform and tools usage for data acquisition, storage, transformation, and analysis.
• Develop roadmaps and implementation strategy around data science initiatives including recommendation engines, predictive modeling, and machine learning.
• Review and audit existing solutions, design, and system architecture.
• Perform profiling and troubleshooting of existing solutions.
• Create technical documentation.

Required Qualifications

• Experience in Non-Functional Testing with experience as a Performance Engineer, with detailed knowledge of Non-Functional Test processes.
• Define Performance Test plans and roadmaps and partner with the Engineering team to deliver strategy.
• Experience building performance environment data sets and using data virtualization tools where required.
• Assess varying priorities and establish critical path and MVP when time constrained.
• Experience installing, configuring, and using Performance Testing tools such as LoadRunner and JMeter.
• Experience with performance monitoring tools.

Embedded within a company-wide Data and Big Data practice, the Big Data Solution Architect designs analytics solutions using the full Data technology stack and leads implementations from requirements through solution go-live. Working closely with customer teams, business stakeholders, and colleagues across seminars and mentoring programs, this role conducts architecture reviews, calculates ROI, and advances the organization's capability to leverage cloud data platforms at scale.

Core Functions

• Work closely with business in identifying solution requirements and key case-studies to architect data solutions for business transformation.
• Participate in Data and Big Data initiatives on a company level.
• Design Data analytics solutions by utilizing the Data technology stack with Big Data techniques.
• Conduct solution architecture review and audit, calculate and present ROI.
• Create and present solution architecture documents with deep technical details to customer and implementation teams.
• Participate in pre-sale activities to prepare technical proposals on customer requests.
• Lead implementation of solutions from establishing project requirements and goals to solution go-live.
• Maintain a strong understanding of industry trends and best practices.
• Share experience, knowledge, and vision with colleagues and customer teams, and participate in seminars, meetups, mentoring, and training programs.

Qualifications and Experience

• Strong hands-on experience as a Data Architect with design and development background in Java, Scala, or Python.
• Architecture experience in Data Management, Data Storage, Data Visualization, Disaster Recovery, Integration, Operation, Presale Support, and Security.
• Experience with building traditional Cloud Data Warehouses and Data Lakes.
• Wide experience in analysis, design, implementation, deployment, troubleshooting, and rebuilding distributed Linux-based platforms and Big Data solutions on premises and in Cloud.
• Strong Cloud experience in at least one of AWS, Azure, or GCP.
• Broad experience with Containers and Resource Management systems including Docker, Mesos, Kubernetes, OpenShift, and Yarn.
• Strong communication skills and experience in team coordination and solution implementation supervision.
• Fluency in English and knowledge of other languages.

Reporting to senior leadership, the Big Data Solution Architect leads the full life-cycle of large-scale Spark-based data solutions, overseeing architecture, data modeling, and client engagement for organizations with 15 to 18 years of complex data processing demands. Partnering with C-level executives, cross-functional delivery teams, and IT consultants, this role shapes data management strategy and produces executive presentations and architecture papers that enable data-driven business transformation.

Primary Duties

• Design and architect large-scale data processing, data storage, and data distribution systems.
• Work with multi-technology and cross-functional teams and customer stakeholders to guide and manage a full life-cycle of a Spark solution.
• Perform data modeling and database design involving Data Warehousing, Business Intelligence systems, and relational and MPP database platforms.
• Handle administration, configuration management, monitoring, and performance tuning of Spark-based platforms.
• Frame architectural decisions and provide technology leadership and direction.
• Develop and maintain strong client relations with senior and C-level executives, delivering actionable and high-impact results.
• Lead and mentor other IT consultants within the practice and across business units.
• Participate in client engagement to develop plans and strategies of data management processes and IT programs.
• Contribute to thought capital through creation of executive presentations, architecture documents, and IT position papers.

Skills and Qualifications

• 15 to 18 years of experience in designing, architecting, and implementing large-scale data processing, data storage, and data distribution systems.
• Extensive experience working with large data sets and building robust Big Data solutions using Spark framework, AWS and GCP Big Data services, and industry-standard frameworks like Databricks.
• Extensive experience in data modeling and database design involving Data Warehousing, Business Intelligence systems, and relational and MPP database platforms.
• Strong understanding of Big Data Analytics platforms and ETL in the context of Big Data, and broad understanding of real-time analytics.
• Technical skills across Hadoop (HDFS, MapReduce, Hive, HBase, Pig, Mahout, Avro, Oozie), NoSQL (Cassandra, MongoDB, HBase, AWS DynamoDB, DocumentDB), and DW platforms (Teradata, Netezza, Greenplum, Vertica, AWS Redshift).
• GCP mandatory skills including BigQuery, Dataflow, Dataproc, Datafusion, DataComposer, and Cloud SQL, and Spark mandatory skills including Databricks, Spark in AWS EMR, and Spark in Azure HDInsight.
• Ability to produce high-quality work products under pressure and within deadlines, and coordinate with developers, architects, and cross-functional teams.

Sitting at the intersection of cloud architecture and enterprise data modernization, the Big Data Solution Architect analyzes customer requests and constructs Big Data solutions using Synapse Analytics, Azure Databricks, and Azure Data Explorer, guiding clients through full migration roadmaps. Operating across pre-sales, discovery, design, and deployment phases, this role produces Databricks Notebooks, designs multi-type data models, and delivers customer-ready documentation that enables informed architectural decisions at scale.

Duties

• Analyze customer requests and produce innovative data solutions and a comprehensive cloud journey for the customer.
• Provide technical leadership, architectural design and diagrams, and hands-on development for data-related project aspects.
• Define and implement technical roadmaps for customers to migrate or modernize their Data Estate using Azure data technologies.
• Design and develop data pipelines and transformations using Azure Data Factory, Apache Spark, or Polybase.
• Create Databricks Notebooks using Scala, Python, DataFrames, SQL, and R.
• Construct Big Data architectures using Synapse Analytics, Azure Databricks, and Azure Data Explorer.
• Design data models of different types including dimensional, semantic, tabular, OLAP, and OLTP.
• Provide expertise in cloud design such as selecting when IaaS or PaaS is the best solution.
• Create customer-ready project documentation, diagrams, architectural documents, and reference materials, and present to internal and external customers.

Experience and Qualifications

• 3+ years of experience designing and implementing enterprise Azure data solutions for Big Data analytics, Data Warehouses, or other large-scale data systems.
• 3+ years of experience with cloud relational data stores and toolsets including Azure SQL, Synapse Analytics, Analysis Services, and Azure Data Factory.
• 5+ years of experience with non-relational data stores including Azure Blob, HDInsight, Data Lake, CosmosDB, Hadoop, and Cloudera.
• 3+ years of experience with Databricks, Delta Lake, and Apache Spark Clusters.
• 8+ years of MS SQL Server experience with strong SQL skills including stored procedures, views, complex joins, columnstore indexes, and performance tuning.
• Expertise in ELT and ETL data transformation strategies, schema-on-write and schema-on-read, Lambda architecture, and Big Data architectures such as Kimball design, normalization, slowly changing dimensions, and parquet.
• Strong knowledge of Business Intelligence tools such as Power BI, Tableau, Cognos, SSRS, and MicroStrategy.
• Experience designing real-time, near real-time, and batch enterprise data pipelines, and constructing solutions based on streaming data such as Kafka and Event Hub.
• Passed or able to quickly pass Microsoft DP-200 and DP-201 Exams to achieve Azure Data Engineer Associate certification.

A key member of a high-performing agile team, the Principal Big Data Solution Architect leads rapid prototyping, full software development lifecycle execution, and delivery of container-based solutions on AWS, collaborating with engineers, software developers, and key stakeholders to verify architecture scalability, security, and compliance. Collaborating across business units and client organizations, this role shapes cloud-native development services and mentors team members to advance next-generation data application capabilities.

Leadership Responsibilities

• Communicate with staff or clients to understand specific system requirements.
• Provide advice on project costs, design concepts, or design changes.
• Document design specifications, installation instructions, and other system-related information.
• Verify stability, interoperability, portability, security, or scalability of system architecture.
• Collaborate with engineers or software developers to select appropriate design solutions or ensure compatibility of system components.
• Lead rapid prototyping of new products to test important customer features or demonstrate to key stakeholders.
• Lead all aspects of the software development lifecycle including estimating, technical design, implementation, documentation, testing, and deployment.
• Provide high-level design and development plan of cloud-based solutions and ensure enterprise-readiness, security, and compliance.
• Deliver container-based solutions as part of cloud migration, app modernization, and cloud-native development services on AWS.

Education and Experience

• Bachelor's degree in Information Technology and Statistics, or 6+ years of hands-on programming experience in lieu of education.
• 4+ years of hands-on programming experience architecting and modernizing next-generation data applications.
• 3+ years of experience building distributed solutions with Kafka, and 2+ years of experience with relational databases.
• 2+ years of experience with Docker, deploying containers, and automated build deployments using Jenkins or AWS Compute and Container Services.
• 2+ years of experience with AWS services including EC2, RDS, IAM, Lambda, SNS, SQS, and S3.
• Experience with Big Data tools including Spark, Python, MongoDB, and NoSQL-based decision systems, and hands-on experience in Hadoop Ecosystem including Spark, Streamsets, MapReduce, and Kafka.
• In-depth knowledge of AWS Storage, Database Services, and AWS Machine Learning services.
• Experience with Data Science toolsets and technology, and hands-on expertise using JS frameworks.
• Advanced ability to mentor team members and demonstrated excellence in written and verbal communication skills.

Scalable and data-driven business outcomes depend on the Big Data Solution Architect, who develops a strategic vision for the company's Big Data platform, evaluates and implements on-premise and cloud technologies, and champions data privacy standards to protect organizational assets. Based within a cross-functional setting that spans business, product, infrastructure, and development teams, this role creates architecture documents, develops proofs-of-concept, and serves as the subject matter expert guiding technical consultations with senior executives.

Strategic Responsibilities

• Be a strong thought leader in Big Data engineering and Big Data architecture.
• Develop a strategic vision and drive the evolution of the company's Big Data platform and analytics capabilities.
• Work with internal and external stakeholders to identify requirements and use-cases, create solutions leveraging Big Data and cloud technologies, and drive technical architecture and implementation plans.
• Provide Big Data subject matter expertise during technical consultations by business and product groups or other solutions architects.
• Evaluate, recommend, design, and implement on-premise and on-cloud Big Data technologies and infrastructure.
• Define standards, policies, and best practices.
• Create architecture and technical design documents to communicate solutions to implementing teams.
• Develop proofs-of-concept, minimum viable products, prototypes, and product demos.
• Champion data privacy and information security laws, policies, and standards.

Background and Experience

• 10 years of broad information technology experience with a proven track record of architecting and building large-scale distributed Big Data systems on-premises and in the cloud.
• Hands-on experience with Hadoop, MPP, NoSQL, or other Big Data platforms, and with Big Data or streaming data tools.
• Hands-on experience with programming languages typically used in Big Data solutions.
• Deep understanding of traditional data warehousing, Business Intelligence, and data management concepts, principles, and techniques.
• Familiarity with the Philippine Data Privacy law.
• Strong analytical and problem-solving skills with the ability to develop creative and efficient solutions.
• Excellent verbal and written communication skills with a high degree of comfort speaking with senior executives at large companies.

As the Big Data Solution Architect, this role introduces unique solutions that transform how client organizations work with data, covering everything from high-level BI architecture to ETL processes, analytical tasks, and dashboard design. The delivery team relies on this work to execute hands-on implementation of Near-Real Time and Batch Data Pipelines using tools such as Databricks, Snowflake, Alteryx, and Tableau in highly regulated environments including Banking and Telecom.

Accountabilities

• Introduce unique solutions with the potential to transform company operations.
• Change the way the client's organization works with data.
• Conduct business analysis and high-level communication with the client in requirement definition.
• Search for and develop new and innovative solutions.
• Design solutions from high-level BI architecture to specific procedures, ETL processes, analytical tasks, reports, and dashboards.
• Handle hands-on involvement in implementation.

Technical Qualifications

• First-hand experience with large-scale Big Data technologies including Hadoop, MapReduce, Hive, HBase, MongoDB, and Cassandra.
• Experience with Impala, Oozie, Mahout, Flume, ZooKeeper, and Sqoop is a benefit.
• Hands-on expertise in Hadoop ecosystems, Databricks, Azure Data Lake Store, Azure Data Factory, and Kafka.
• End-to-end design and build of Near-Real Time and Batch Data Pipelines.
• High level of proficiency in data analysis using SQL or equivalent.
• Experience with Databricks, Snowflake, Alteryx, and Tableau is a great advantage.
• Fundamental understanding of R, Python, Jupyter Notebook, RStudio, R Shiny, or DataIKU DSS.
• Experience working in highly regulated environments such as Banking or Telecom.
• Strong written and verbal communication skills, and experience working alongside internal and external stakeholders and technology partners.