Data Architect

Data Architect

The selected candidate

• Leads the design and implementation of processes to extract transform and load datafrom disparate sources into a form that is consumable by analytics processes for largeor more complex projects using advanced technical capabilities
• Takes accountability for the production of a suite of data models with relatively highcomplexity leveraging a strong understanding of data modelling standards to ensurehigh 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 businessvalue as well as interfacing and communicating with program teams management andstakeholders to deliver large complex projects

Your key responsibilities include

• Leading the design development and implementation of processes to extracttransform and load data from disparate sources into a form that is consumable byanalytics processes within a given project reviewing deliverables to ensure highquality
• 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 intodetailed design specifications
• Define and implement data management strategies to align with business objectives
• Evaluating and resolving issues regarding data quality reviews cleansing dataintegration and migration leveraging advanced technical knowledge and showingtechnical leadership in aspects of data engineering while driving continuous improvement efforts
• Providing a leadership role for the work group ensuring the appropriate expectationsprinciples structures tools and responsibilities are in place to deliver the project
• Analyzing the latest industry trends such as cloud computing and distributedprocessing and inferring potential impact on businesses (short and long-term)
• Providing advanced technical expertise to maximize efficiency reliability and valuefrom current data engineering processes. Researching and monitoring existing clientbase and industry developments to identify potential new product opportunities fromemerging technologies
• Developing strong working relationships with peers across engineering collaboratingto develop leading data engineering solutions
• Driving adherence to the relevant data engineering and data modeling processesprocedures standards and may input into the definition maintenance andimplementation 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 InfrastructureArchitecture 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 businessrequirements 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 ofdata where a group of transactions is collected over a period of time
• Data Integration (Sourcing Storage and Migration) - Capability to design andimplement models capabilities and solutions to manage data within the enterprise(structured and unstructured data archiving principles data warehousing datasourcing 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 toestablish its quality against a defined set of parameters and to highlight data wherecorrective action (cleansing) is required to remediate the data
• Stream Systems - Capability to discover integrate and ingest all available data fromthe machines that produce it as fast as its 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 Ingestiontransformation 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 databasesthat 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 usingseveral 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 4J 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 fieldpreferred
• 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 andpassion
• 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

We offer a competitive remuneration package where youll be rewarded for yourindividual and team performance. Our comprehensive Total Rewards package includessupport for flexible working and career development and with FlexEY you can selectbenefits that suit your needs covering holidays health and well-being insurance savingsand a wide range of discounts offers and promotions. Plus we offer:

• 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 thats right for you