EY
At EY, we’re all in to shape your future with confidence.
We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.
The opportunity EY is a global leader in assurance, tax, transaction and advisory services. Technology is at the heart of what we do and deliver at EY. Client Technology seeks to drive growth opportunities and solve complex business problems for our clients through building a robust platform for business and a powerful product engine that are vital to innovation at scale.
As part of Client Technology, you’ll work with technologists and business experts, blending EY’s deep industry knowledge and innovative ideas with our platforms, capabilities, and technical expertise.
As a catalyst for change and growth, you’ll be at the forefront of integrating emerging technologies from AI to Data Analytics into every corner of what we do at EY. That means more growth for you, exciting learning opportunities, career choices, and the chance to make a real impact.
The selected candidate
Hands‑on with design and implementation of scalable data pipelines, ETL processes, and data warehousing solutions aligned with Azure Well‑Architected Framework (WAF) pillars.
Accountable for a suite of data models with relatively high complexity and a strong understanding of data modelling standards to ensure high quality.
Drive best practices for data security, data privacy, and data integrity.
Ensure the reliability and efficiency of data infrastructure in the Azure cloud.
Understand AI‑driven data engineering tools and build cutting‑edge AI use cases, ensuring availability of AI‑ready data.
Work with other departments to define and deliver business value, interfacing and communicating with program teams, management, and stakeholders to deliver large, complex projects.
Your Key Responsibilities Include
Lead the production of high‑quality data engineering deliverables, ensuring project timelines are met and providing informal mentoring and training to junior team members.
Lead the design, development, and implementation of processes to extract, transform, and load data from disparate sources into a form consumable by analytics.
Develop and define future‑state data architectures aligned with industry best practices and organizational needs.
Design and implement data architecture strategy, assess existing data architecture, and devise recommendations.
Lead translation of requirements, design, and solution architecture deliverables into detailed design specifications.
Define and implement data management strategies aligned with business objectives.
Lead delivery of data quality reviews, including data cleansing where required to ensure integrity and quality.
Evaluate and resolve issues related to data quality, cleansing, integration, and migration, showing technical leadership.
Provide a leadership role for the work group, ensuring expectations, principles, structures, tools, and responsibilities are in place to deliver the project.
Analyze the latest industry trends such as cloud computing and distributed processing and infer potential impact on businesses.
Provide advanced technical expertise to maximize efficiency, reliability, and value from current data engineering processes; research and monitor client base and industry developments for new product opportunities.
Develop strong working relationships with peers across engineering, collaborating to build leading data engineering solutions.
Drive adherence to relevant data engineering and data modeling processes, procedures, standards, and input into technology standards definition and implementation.
Skills And Attributes For Success
Data Architecture: design and implement solutions that meet organizational needs using Azure WAF pillars.
Infrastructure Architecture Diagrams: create and deliver Azure Infrastructure Architecture Diagrams (IAD) that clearly represent the architecture of data solutions.
Data Extraction & Ingestion: design efficient strategies for high‑volume structured and unstructured data extraction and streaming ingestion.
Data Processing & Modeling: design and implement models, validation, quality, profiling, and complex data models.
Data Store & Governance: design storage models, migration, consumption mechanisms, and governance mechanisms including catalog, lineage, classification, MDM, and exploration.
Data Security: design and implement authentication and authorization to ensure data security.
Required Technical Skills
Hands‑on experience building Data Architecture using patterns such as Data Mesh, Data Fabric, Data Lakehouse, Data observability, and Data as a Service (DaaS).
Proficient in Azure services (Azure Data Lake, Azure SQL Database, Azure Synapse Analytics) for scalable, efficient solutions.
Experience building data orchestration through Azure Data Factory, Function App, Logic App.
Proficient in SQL and programming languages such as Python and Java.
Extensive experience optimizing Databricks performance (ingestion, transformation, consumption).
Experience designing and building Data Platforms integrating disparate data sources.
Experience designing authentication and authorization methods for data security.
Expertise in MPP designs to accelerate performance of large databases.
Expertise in Azure, Azure Databricks, Azure SQL, Spark.
Expertise developing dataflows using NiFi, ADF, Databricks.
Advanced design and implementation experience of large analytical warehouses.
Experience with Spark architecture and implementation methods.
Experience working with Distributed Message Systems like Kafka.
Hands‑on experience with Python, PySpark, or R.
Expert in creating and analyzing complex SQL queries and procedures.
Understanding of Big Data and distributed architecture.
Experience creating ingestion workflows using Oozie or similar tools.
Knowledge of security measures such as HTTPS and Kerberos.
Beneficial Technical Skills
Azure Data Lake Storage, Databricks Delta Lakes.
Experience with NoSQL databases.
Advanced Analytics, ML, and AI.
Knowledge of graph databases (Neo4J, Cypher, CosmosDB).
Experience developing microservices.
Education
B.E. / M.S. in Computer Science, Data Analytics, Data Science, Engineering, IT, or related field (preferred).
Big Data certification from Cloudera, Hortonworks, or Databricks (preferred).
What We Look For
Strong analytical skills and problem‑solving ability.
Self‑starter, independent thinker, curious, creative, ambitious, and passionate.
Excellent interpersonal, communication, collaboration, and presentation skills.
Customer‑focused.
Excellent time‑management skills.
Positive and constructive mindset.
Commitment to continuous self‑learning.
Leadership and decision‑making in critical situations.
Attention to detail.
High levels of integrity and honesty.
What We Offer You The compensation ranges below are provided in order to comply with United States pay transparency laws. Other geographies will follow local salary guidelines.
Comprehensive compensation and benefits package based on performance, including medical and dental coverage, pension and 401(k) plans, and a range of paid time off.
Hybrid workplace model: most external, client‑serving roles work together in person 40–60% of the time.
Flexible vacation policy: choose how much vacation to take; time off for EY Paid Holidays, winter/summer breaks, personal/family care, and other leaves.
Are you ready to shape your future with confidence? Apply today. EY accepts applications for this position on an ongoing basis.
For those living in California, please
click here for additional information .
EY focuses on high‑ethical standards and integrity. We expect all candidates to demonstrate these qualities.
Equal Employment Opportunity EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or arrest and conviction records, in accordance with applicable law.
EY is committed to providing reasonable accommodation to qualified individuals with disabilities, including veterans with disabilities. If you have a disability and need assistance applying online or request accommodation during any part of the application process, please call 1‑800‑EY‑HELP3, select Option 2 for candidate‑related inquiries, then Option 1 for candidate queries, and finally Option 2 for candidates with an inquiry. Alternatively, email the TSS at ssc.customersupport@ey.com.
Seniority level Director
Employment type Full‑time
Job function Engineering and Information Technology
Industries Professional Services
Referrals increase your chances of interviewing at EY by 2x.
#J-18808-Ljbffr
We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.
The opportunity EY is a global leader in assurance, tax, transaction and advisory services. Technology is at the heart of what we do and deliver at EY. Client Technology seeks to drive growth opportunities and solve complex business problems for our clients through building a robust platform for business and a powerful product engine that are vital to innovation at scale.
As part of Client Technology, you’ll work with technologists and business experts, blending EY’s deep industry knowledge and innovative ideas with our platforms, capabilities, and technical expertise.
As a catalyst for change and growth, you’ll be at the forefront of integrating emerging technologies from AI to Data Analytics into every corner of what we do at EY. That means more growth for you, exciting learning opportunities, career choices, and the chance to make a real impact.
The selected candidate
Hands‑on with design and implementation of scalable data pipelines, ETL processes, and data warehousing solutions aligned with Azure Well‑Architected Framework (WAF) pillars.
Accountable for a suite of data models with relatively high complexity and a strong understanding of data modelling standards to ensure high quality.
Drive best practices for data security, data privacy, and data integrity.
Ensure the reliability and efficiency of data infrastructure in the Azure cloud.
Understand AI‑driven data engineering tools and build cutting‑edge AI use cases, ensuring availability of AI‑ready data.
Work with other departments to define and deliver business value, interfacing and communicating with program teams, management, and stakeholders to deliver large, complex projects.
Your Key Responsibilities Include
Lead the production of high‑quality data engineering deliverables, ensuring project timelines are met and providing informal mentoring and training to junior team members.
Lead the design, development, and implementation of processes to extract, transform, and load data from disparate sources into a form consumable by analytics.
Develop and define future‑state data architectures aligned with industry best practices and organizational needs.
Design and implement data architecture strategy, assess existing data architecture, and devise recommendations.
Lead translation of requirements, design, and solution architecture deliverables into detailed design specifications.
Define and implement data management strategies aligned with business objectives.
Lead delivery of data quality reviews, including data cleansing where required to ensure integrity and quality.
Evaluate and resolve issues related to data quality, cleansing, integration, and migration, showing technical leadership.
Provide a leadership role for the work group, ensuring expectations, principles, structures, tools, and responsibilities are in place to deliver the project.
Analyze the latest industry trends such as cloud computing and distributed processing and infer potential impact on businesses.
Provide advanced technical expertise to maximize efficiency, reliability, and value from current data engineering processes; research and monitor client base and industry developments for new product opportunities.
Develop strong working relationships with peers across engineering, collaborating to build leading data engineering solutions.
Drive adherence to relevant data engineering and data modeling processes, procedures, standards, and input into technology standards definition and implementation.
Skills And Attributes For Success
Data Architecture: design and implement solutions that meet organizational needs using Azure WAF pillars.
Infrastructure Architecture Diagrams: create and deliver Azure Infrastructure Architecture Diagrams (IAD) that clearly represent the architecture of data solutions.
Data Extraction & Ingestion: design efficient strategies for high‑volume structured and unstructured data extraction and streaming ingestion.
Data Processing & Modeling: design and implement models, validation, quality, profiling, and complex data models.
Data Store & Governance: design storage models, migration, consumption mechanisms, and governance mechanisms including catalog, lineage, classification, MDM, and exploration.
Data Security: design and implement authentication and authorization to ensure data security.
Required Technical Skills
Hands‑on experience building Data Architecture using patterns such as Data Mesh, Data Fabric, Data Lakehouse, Data observability, and Data as a Service (DaaS).
Proficient in Azure services (Azure Data Lake, Azure SQL Database, Azure Synapse Analytics) for scalable, efficient solutions.
Experience building data orchestration through Azure Data Factory, Function App, Logic App.
Proficient in SQL and programming languages such as Python and Java.
Extensive experience optimizing Databricks performance (ingestion, transformation, consumption).
Experience designing and building Data Platforms integrating disparate data sources.
Experience designing authentication and authorization methods for data security.
Expertise in MPP designs to accelerate performance of large databases.
Expertise in Azure, Azure Databricks, Azure SQL, Spark.
Expertise developing dataflows using NiFi, ADF, Databricks.
Advanced design and implementation experience of large analytical warehouses.
Experience with Spark architecture and implementation methods.
Experience working with Distributed Message Systems like Kafka.
Hands‑on experience with Python, PySpark, or R.
Expert in creating and analyzing complex SQL queries and procedures.
Understanding of Big Data and distributed architecture.
Experience creating ingestion workflows using Oozie or similar tools.
Knowledge of security measures such as HTTPS and Kerberos.
Beneficial Technical Skills
Azure Data Lake Storage, Databricks Delta Lakes.
Experience with NoSQL databases.
Advanced Analytics, ML, and AI.
Knowledge of graph databases (Neo4J, Cypher, CosmosDB).
Experience developing microservices.
Education
B.E. / M.S. in Computer Science, Data Analytics, Data Science, Engineering, IT, or related field (preferred).
Big Data certification from Cloudera, Hortonworks, or Databricks (preferred).
What We Look For
Strong analytical skills and problem‑solving ability.
Self‑starter, independent thinker, curious, creative, ambitious, and passionate.
Excellent interpersonal, communication, collaboration, and presentation skills.
Customer‑focused.
Excellent time‑management skills.
Positive and constructive mindset.
Commitment to continuous self‑learning.
Leadership and decision‑making in critical situations.
Attention to detail.
High levels of integrity and honesty.
What We Offer You The compensation ranges below are provided in order to comply with United States pay transparency laws. Other geographies will follow local salary guidelines.
Comprehensive compensation and benefits package based on performance, including medical and dental coverage, pension and 401(k) plans, and a range of paid time off.
Hybrid workplace model: most external, client‑serving roles work together in person 40–60% of the time.
Flexible vacation policy: choose how much vacation to take; time off for EY Paid Holidays, winter/summer breaks, personal/family care, and other leaves.
Are you ready to shape your future with confidence? Apply today. EY accepts applications for this position on an ongoing basis.
For those living in California, please
click here for additional information .
EY focuses on high‑ethical standards and integrity. We expect all candidates to demonstrate these qualities.
Equal Employment Opportunity EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or arrest and conviction records, in accordance with applicable law.
EY is committed to providing reasonable accommodation to qualified individuals with disabilities, including veterans with disabilities. If you have a disability and need assistance applying online or request accommodation during any part of the application process, please call 1‑800‑EY‑HELP3, select Option 2 for candidate‑related inquiries, then Option 1 for candidate queries, and finally Option 2 for candidates with an inquiry. Alternatively, email the TSS at ssc.customersupport@ey.com.
Seniority level Director
Employment type Full‑time
Job function Engineering and Information Technology
Industries Professional Services
Referrals increase your chances of interviewing at EY by 2x.
#J-18808-Ljbffr