Data Engineer Assistant Director

Job description

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. Technology solutions are integrated in the client services we deliver and are key to our innovation as an organization.

Fueled by strategic investment in technology and innovation, Client Technology seeks to drive growth opportunities and solve complex business problems for our clients through building a robust platform for business and 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

·  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
·  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
·  Leading translation of requirements, design and solution architecture deliverables into detailed design specifications
·  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

·  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

·  Experience designing and building Data Platforms integrating disparate data sources
·  Knowledge of Core Java/Scala
·  Expertise in Data Architecture, ETL, SQL
·  Expertise in working with MPP designs to speed the performance of huge databases that deal with massive amounts of data
·  Expertise in Azure, Azure Databricks, Azure SQL, Spark
·  Expertise developing dataflows using NiFi/ADF, Databricks
·  Advanced, hands-on design experience implementing large analytic warehouses
·  Advanced, hands-on experience in Spark architecture and implementation using several 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
·  Knowledge of creating ingestion workflows using Oozie or similar tools
·  Knowledge of security measures like HTTPS and Kerberos

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

 

We offer a competitive remuneration package where you’ll be rewarded for your individual and team performance. Our comprehensive Total Rewards package includes support for flexible working and career development, and with FlexEY you can select benefits that suit your needs, covering holidays, health and well-being, insurance, savings and 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 that’s right for you

EY is committed to being an inclusive employer and we are happy to consider flexible working arrangements. We strive to achieve the right balance for our people, enabling us to deliver excellent client service whilst allowing you to build your career without sacrificing your personal priorities.