Ernst & Young - Raleigh, NC

posted about 2 months ago

Full-time - Senior
Raleigh, NC
Professional, Scientific, and Technical Services

About the position

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we're counting on your unique voice and perspective to help EY become even better. Join us and build an exceptional experience for yourself, and a better working world for all. The exceptional EY experience. It's yours to build. EY focuses on high-ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities. The opportunity EY is seeking for Senior Data Engineer ingests, builds, and supports large-scale data architectures that serve multiple downstream systems and business users. This individual supports the Data Engineer Leads and partners with Visualization on data quality and troubleshooting needs. As a Senior Data Engineer, you will design, develop, optimize, and maintain data architecture and pipelines that adhere to ETL principles and business goals. You will develop and maintain scalable data pipelines, build out new integrations using AWS native technologies to support continuing increases in data source, volume, and complexity. You will define data requirements, gather and mine large scale of structured and unstructured data, and validate data by running various data tools in the Big Data Environment. Additionally, you will support standardization, customization and ad hoc data analysis and develop the mechanisms to ingest, analyze, validate, normalize, and clean data. You will write unit/integration/performance test scripts and perform data analysis required to troubleshoot data related issues and assist in the resolution of data issues. Implementing processes and systems to drive data reconciliation and monitor data quality will be crucial, ensuring production data is always accurate and available for key stakeholders, downstream systems, and business processes. You will lead the evaluation, implementation and deployment of emerging tools and processes for analytic data engineering to improve productivity. Furthermore, you will develop and deliver communication and education plans on analytic data engineering capabilities, standards, and processes. In this role, you will learn about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics, solving complex data problems to deliver insights that help achieve business objectives. You will partner with Business Analytics and Solution Architects to develop technical architectures for strategic enterprise projects and initiatives, coordinate with Data Scientists to understand data requirements, and design solutions that enable advanced analytics, machine learning, and predictive modelling. You will also support Data Scientists in data sourcing and preparation to visualize data and synthesize insights of commercial value, collaborate with AI/ML engineers to create data products for analytics and data scientist team members to improve productivity, and advise, consult, mentor and coach other data and analytic professionals on data standards and practices, promoting the values of learning and growth. Fostering a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions will be key to your success in this role.

Responsibilities

  • Design, develop, optimize, and maintain data architecture and pipelines that adheres to ETL principles and business goals.
  • Develop and maintain scalable data pipelines, build out new integrations using AWS native technologies to support continuing increases in data source, volume, and complexity.
  • Define data requirements, gather and mine large scale of structured and unstructured data, and validate data by running various data tools in the Big Data Environment.
  • Support standardization, customization and ad hoc data analysis and develop the mechanisms to ingest, analyze, validate, normalize, and clean data.
  • Write unit/integration/performance test scripts and perform data analysis required to troubleshoot data related issues and assist in the resolution of data issues.
  • Implement processes and systems to drive data reconciliation and monitor data quality, ensuring production data is always accurate and available for key stakeholders, downstream systems, and business processes.
  • Lead the evaluation, implementation and deployment of emerging tools and processes for analytic data engineering to improve productivity.
  • Develop and deliver communication and education plans on analytic data engineering capabilities, standards, and processes.
  • Learn about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics.
  • Solve complex data problems to deliver insights that help achieve business objectives.
  • Implement statistical data quality procedures on new data sources by applying rigorous iterative data analytics.

Requirements

  • Bachelor's degree in Engineering, Computer Science, Data Science, or related field.
  • 5+ years of experience in software development, data science, data engineering, ETL, and analytics reporting development.
  • Experience designing, building, implementing, and maintaining data and system integrations using dimensional Datamodelling and development and optimization of ETL pipelines.
  • Proven track record of designing and implementing complex data solutions.
  • Demonstrated understanding and experience using Data Engineering Programming Languages (ie, Python).
  • Experience with Distributed Data Technologies (eg, Pyspark).
  • Experience with Cloud platform deployment and tools (eg, Kubernetes).
  • Experience with Relational SQL databases.
  • Experience with DevOps and continuous integration.
  • Experience with AWS cloud services and technologies (ie, Lambda, S3, DMS, Step Functions, Event Bridge, Cloud Watch, RDS).
  • Experience with Databricks/ETL IICS/DMS GitHub Event Bridge, Tidal.
  • Strong organizational skills with the ability to manage multiple projects simultaneously and operate as a leading member across globally distributed teams to deliver high-quality services and solutions.
  • Understanding of database architecture and administration processes.
  • High proficiency in code programming languages (eg, SQL, Python, Pyspark, AWS services) to design, maintain, and optimize data architecture/pipelines that fit business goals.
  • Ability to extract, transform, and load data from multiple external/internal sources using Databricks Lakehouse/Data Lake concepts into a single, consistent source to serve business users and data visualization needs.
  • Utilization of the principles of continuous integration and delivery to automate the deployment of code changes to elevate environments, fostering enhanced code quality, test coverage, and automation of resilient test cases.
  • Excellent written and verbal communication skills, including storytelling and interacting effectively with multifunctional teams and other strategic partners.
  • Strong problem solving and troubleshooting skills.
  • Ability to work in a fast-paced environment and adapt to changing business priorities.

Nice-to-haves

  • Experience in leading and influencing teams, with a focus on mentorship and professional development.
  • A passion for innovation and the strategic application of emerging technologies to solve real-world challenges.
  • The ability to foster an inclusive environment that values diverse perspectives and empowers team members.

Benefits

  • Comprehensive compensation and benefits package based on performance.
  • Medical and dental coverage.
  • Pension and 401(k) plans.
  • Wide range of paid time off options including designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence.
  • Flexible vacation policy allowing you to decide how much vacation time you need based on personal circumstances.
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