Principal Information Architect - Data Integration

Principal Information Architect, Data Integration

Job Summary

At CSX, a data integration architect operates within the sphere of data management and cloud computing, offering expertise in crafting data strategies that align with business goals. The individual must have vast knowledge of Azure, AWS or Google cloud services. Ensure that data from disparate sources is coherently combined, leveraging various frameworks, methodologies and cloud design patterns. The resulting integration must be designed to strengthen business strategies by leveraging data and cloud architecture. As CSX becomes more data-driven, the data integration architect must collaborate closely with internal stakeholders, ensuring that data integration mirrors business requirements. The data integration architect is responsible for shaping and then adhering to CSX’s data strategy and driving business intelligence efforts. This role is crucial since it bridges the gap between raw data and actionable insights, ensuring that businesses are truly utilizing those insights to drive data-driven business decisions.

Job Responsibilities

• Technical Proficiency (Knowledge of ETL Tools, Databases, and Cloud Platforms): A data architect is highly skilled in using ETL tools, databases, and cloud platforms. They excel in optimizing data flow through ETL processes, ensuring seamless integration of data from various sources into a cohesive data data lake architecture. They have a strong foundation in SQL, relational databases like SQL Server, and data modeling techniques. As businesses increasingly migrate to the cloud, proficiency in platforms such as Azure and understanding cloud computing data processing becomes pivotal. Familiarity with programming languages, especially Python and Java, often comes into play, especially when creating custom data solutions.
• Analytical Thinking and Problem-solving: In the complex realm of big data, unforeseen challenges are the norm. From inconsistencies in data quality to roadblocks in data integration, architects need robust problem-solving skills. Their role often overlaps with data scientists and data analysts in this regard, using data analytics tools and methodologies to derive insights and address anomalies. Their analytical thinking enables effective data mining and the development of data-driven solutions aligned with business requirements.
• Strong Communication Skills: Beyond technical know-how, excellent communication skills are paramount. Data integration architects often collaborate with internal stakeholders, understanding and translating business requirements into technical specifications. Their soft skills enable them to bridge the gap between IT teams, data engineers, and business units, ensuring a harmonious and agile project lifecycle.
• Project Management and Coordination Abilities: Overseeing a data integration strategy isn’t a solitary task. Architects often wear the hat of a project manager, coordinating between teams, setting timelines, and ensuring deliverables align with the outlined business intelligence objectives. Their understanding of methodologies like Agile and DevOps ensures that projects remain adaptable and iterative, in sync with evolving business goals.
• Understanding of Data Privacy and Compliance Issues: In the era of GDPR and other data protection regulations, architects go beyond integration. They are responsible for data governance and security. Their expertise ensures adherence to certifications and compliance standards. Balancing accessibility with security, they employ data management systems that prioritize data privacy while catering to business's data visualization and decision-making needs.
• Enhancing Data Flow and Accessibility: One of the primary responsibilities of a data integration architect is to ensure smooth data flow across various platforms and systems. Leveraging tools such as ETL (Extract, Transform, Load) and cloud platforms like Azure optimize data infrastructures. Their knowledge in SQL, data warehousing (data lake bronze, silver and gold layer), and data modeling ensures that data from disparate sources can be accessed easily and efficiently. By interfacing with APIs, and understanding relational databases such as SQL Server, they provide businesses with a seamless flow of data, catering to real-time business needs.
• Reducing Data Silos and Ensuring Data Consistency: Fragmented data, spread across isolated systems or "silos", can be a major roadblock for businesses. Data integration architects play a crucial role in overcoming these barriers. They ensure data consistency by aligning data across departments and systems with business goals. With expertise in metadata management and data governance, they provide standardized and high-quality data throughout the organization.
• Boosting Decision-making Capabilities through Integrated Data Insights: As businesses lean heavily on data analytics and business intelligence tools to drive decisions, the role of a data integration architect becomes even more crucial. Their skills in data visualization, data analysis, and their collaboration with data scientists ensure that integrated data insights are available at decision-makers’ fingertips. Whether it’s leveraging machine learning algorithms or employing data mining techniques, architects play a pivotal role in empowering businesses with actionable insights.
• Facilitating the Successful Deployment of Data-Driven Projects: In agile business environments, the swift deployment of projects is key. Data integration architects, familiar with Agile and DevOps methodologies, ensure that data-driven projects are rolled out efficiently. By understanding business requirements and collaborating with stakeholders, they align project objectives with data strategy. Their technical proficiency, from programming languages such as Python and Java to software engineering principles, ensures that projects not only align with business objectives but also stand the test of technological evolution.
• Exploring Multifaceted and Varied Data Environments: CSX’s data landscape consist of numerous sources that produce vast amounts of data rapidly. Experts in data integration, skilled in data design and structure, tackle the complexities within these varied environments. Their expertise in different data management systems, whether Microsoft or open source, is continually challenged while they navigate through different data infrastructures to maintain smooth data integration.
• Balancing Legacy and Innovation in System Integration: Legacy systems are essential yet frequently problematic. Architects must navigate the demands of business leaders against technical constraints. Mastery of SQL, data warehousing, data lake and relational databases such as SQL Server is vital. Working alongside data engineers, they make certain that new system integrations are smooth and maintain high standards of data quality and integrity.
• Balancing Data Security with Accessibility: Data breaches can spell doom for enterprises and architects are always on their toes ensuring data security. They tread the fine line between ensuring accessibility for data-driven decision-making and fortifying data against malicious threats. Their role often extends beyond the realms of data governance, diving deep into data security protocols, especially when working on cloud platforms like Azure.
• Continuous Adaptation to Evolving Technologies and Industry Standards: As technology evolves, architects must keep up with emerging trends like machine learning, advancements in programming languages, and shifting software engineering methodologies. Clear and up-to-date knowledge is key. Their work experience, often spanning years, needs to be complemented with continuous learning. Adapting to new frameworks, understanding the nuances of DevOps, or simply aligning with changing business goals, the journey of a data integration architect is one of perpetual growth and adaptation.

Minimum Qualifications

• Bachelors degree from an accredited institution required in Computer Science, Computer Engineering, Software Engineering, Information Systems/Technology or related major field of study.
• 10 or more years of experience required in cloud technologies – specifically Azure.

Equivalent Qualifications

• High School diploma/GED.
• 15 or more years of experience in cloud technologies with most of the experience in Azure.

Knowledge and Skills

• Ability to quickly learn the latest information management technologies, become an expert and disseminate to the organization
• Strong technical knowledge and experience with multiple database technologies that include but not limited to SQL Server, Oracle, PostgreSQL, Azure data lake storage (ADLS)
• Advanced Data Integration skills and knowledge in the cloud
• Understanding of data requirements in complex environments
• Interfacing with Technology leadership and ability to communicate appropriately at this level
• Expertise in big data design using high level security and compliance methods
• Excellent ability to adequately and positively influence others
• Experience with Azure Big Data Technologies and various Application Development technologies
• Experience with data management technologies that includes XML, semantic matching, data analysis, data standardization, ETL, data integration, data profiling, data cleansing and metadata management
• Experience with Data Architecture Design and Implementation
• Information expert for multiple business function / technical areas
• Ability to effectively communicate in oral and written mediums with all levels of audiences
• Application development experience and skills
• System documentation skills and data flow diagram skills
• Meticulous in approach to work and outstanding attention to detail
• Time management and organizational planning skills
• Ability to handle multiple tasks and priorities
• Ability to collaborate with team members to meet project deadlines and milestones
• Willingness to learn new technologies
• Excellent oral and written communication skills
• Data Analytical skills
• Excellent customer service skills
• Knowledge of system development life cycles and methodologies
• Strong problem solving skills