Data Architect

Data Architect

The selected candidate

• Leads the design and implementation of processes to extract, transform and load data from disparate sources into a form that is consumable by analytics processes, for large or more complex projects, using advanced technical capabilities
• Takes accountability for the production of a suite of data models with relatively high complexity, leveraging a strong understanding of data modelling standards to ensure high quality
• Drive best practices for data security, privacy, and integrity
• Ensure the reliability and efficiency of data infrastructure in the Azure cloud
• Works with other departments across the business to help define and deliver business value, as well as interfacing and communicating with program teams, management and stakeholders to deliver large, complex projects
  

Your Key Responsibilities Include

• Leading the design, development and implementation of processes to extract, transform and load data from disparate sources into a form that is consumable by analytics processes within a given project, reviewing deliverables to ensure high quality
• Develop and define future state data architectures aligned with industry best practices and organizational needs
• Proficient in designing Data Architecture strategy, developing data architecture for modern data platform, assessing enterprise existing data architecture and devise recommendations
• Leading translation of requirements, design and solution architecture deliverables into detailed design specifications
• Define and implement data management strategies to align with business objectives
• Evaluating and resolving issues regarding data quality reviews, cleansing, data integration and migration, leveraging advanced technical knowledge and showing technical leadership in aspects of data engineering while driving continuous improvement efforts
• Providing a leadership role for the work group, ensuring the appropriate expectations, principles, structures, tools and responsibilities are in place to deliver the project
• Analyzing the latest industry trends such as cloud computing and distributed processing and inferring potential impact on businesses (short and long-term)
• Providing advanced technical expertise to maximize efficiency, reliability and value from current data engineering processes. Researching and monitoring existing client base and industry developments to identify potential new product opportunities from emerging technologies
• Developing strong working relationships with peers across engineering, collaborating to develop leading data engineering solutions
• Driving adherence to the relevant data engineering and data modeling processes, procedures, standards, and may input into the definition, maintenance and implementation of technology standards
  

Skills And Attributes For Success

• Data Architecture: Able to design and implement data architecture solutions that meet organizational needs by leveraging the Azure Well-Architected Framework (WAF) pillars (Cost Optimization, Operational Excellence, Performance Efficiency, Reliability, and Security)
• Data Security: Able to design and implement various authentication and authorization methods to ensure Data security
• Infrastructure Architecture Diagrams: Able to create and deliver Azure Infrastructure Architecture Diagrams (IAD) that visually represent the architecture of data solutions, ensuring clarity and alignment with best practices.
• Data Modeling: Create and maintain comprehensive data models that reflect business requirements and support data governance.
• Data Integration: Develop and manage data integration strategies, including ETL processes, to ensure seamless data flow and accessibility across systems.
• Performance Optimization: Monitor and optimize data store performance (Includes Data Lake, Lakehouse & Data warehouse), ensuring efficient data retrieval and processing
• Data Governance: Implement data governance policies and practices to ensure data quality, security, and compliance with regulations.
• Batch Processing - Capability to design an efficient way of processing high volumes of data where a group of transactions is collected over a period of time
• Data Integration (Sourcing, Storage and Migration) - Capability to design and implement models, capabilities and solutions to manage data within the enterprise (structured and unstructured, data archiving principles, data warehousing, data sourcing, etc.). This includes the data models, storage requirements and migration of data from one system to another
• Data Quality, Profiling and Cleansing - Capability to review (profile) a data set to establish its quality against a defined set of parameters and to highlight data where corrective action (cleansing) is required to remediate the data
• Stream Systems - Capability to discover, integrate, and ingest all available data from the machines that produce it, as fast as it’s produced, in any format, and at any quality
  

Required Technical Skills

• Handson experience in building Data Architecture using various data architecture patterns like Data Mesh, Data Fabric, Data Lakehouse, Data observability & Data as a Service (DaaS)
• Proficient in Azure services (e.g., Azure Data Lake, Azure SQL Database, Azure Synapse Analytics) to build scalable and efficient data solutions.
• Experience in design and development of various authentication and authorization methods to ensure data security
• Proficient in SQL and familiar with programming languages such as Python and Java
• Extensively worked on Databricks performance optimization (includes data Ingestion, transformation and consumption areas)
• Experience designing and building Data Platforms integrating disparate data sources
• Expertise in working with MPP designs to speeds the performance of huge databases that deal with massive amounts of data
• Expertise in Azure, Azure Data Bricks, Azure SQL, Spark
• Expertise developing dataflows using NiFi/ADF, Databricks
• Advanced, hands-on design experience on implemented large analytic warehouse.
• Advanced, hands-on experience in Spark architecture and implementation using several methods
• Experience in working with Distributed Message Systems like Kafka.
• Hands on experience on Python, Pyspark Or R.
• Expert in creating and analyzing complex sql queries and procedures.
• Understanding of big data and distributed Architecture.
• Creating Ingestion workflows using Oozie or similar tools
• Knowledge of security measures like HTTPS and Kerbero
  

Beneficial Technical Skills

• Experience using NoSQL databases.
• Advanced Analytics, ML and AI
• Knowledge in Graph Databases, preferably Neo4J, Cypher and cosmos DB. Neo4J and Graph Data Modeling
• Azure Data Lake Store, Databricks Delta lakes.
• Experience developing Microservices
  

Education

• M.S. Computer Science, Data Analytics, Data Science, Engineering, IT, or related field preferred
• Big Data Certification from either Cloudera/Hortonworks/Databricks
  

What We Look For

• Strong analytical skills and problem-solving ability
• A self-starter, independent-thinker, curious and creative person with ambition and passion
• Excellent inter-personal, communication, collaboration, and presentation skills
• Customer focused
• Excellent time management skills
• Positive and constructive minded
• Takes responsibility for continuous self-learning
• Takes the lead and makes decisions in critical times and tough circumstances
• Attention to detail
• High levels of integrity and honesty
  

What Working At EY Offers

• Support, coaching and feedback from some of the most engaging colleagues around
• Opportunities to develop new skills and progress your career
• The freedom and flexibility to handle your role in a way that’s right for you
  

EY | Building a better working world