Ernst & Young - Chicago, IL

posted about 2 months ago

Full-time - Senior
Chicago, IL
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. EY is seeking a Senior Data Engineer who will be responsible for ingesting, building, and supporting large-scale data architectures that serve multiple downstream systems and business users. This individual will support the Data Engineer Leads and partner with Visualization on data quality and troubleshooting needs. The role involves designing, developing, optimizing, and maintaining data architecture and pipelines that adhere to ETL principles and business goals. The Senior Data Engineer 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. They 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. The role also includes supporting standardization, customization, and ad hoc data analysis, as well as developing mechanisms to ingest, analyze, validate, normalize, and clean data. Additionally, the Senior Data Engineer will write unit/integration/performance test scripts and perform data analysis required to troubleshoot data-related issues, assisting in the resolution of these issues. They will 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. The role requires leading the evaluation, implementation, and deployment of emerging tools and processes for analytic data engineering to improve productivity, as well as developing and delivering communication and education plans on analytic data engineering capabilities, standards, and processes. The position also involves solving complex data problems to deliver insights that help achieve business objectives and implementing statistical data quality procedures on new data sources by applying rigorous iterative data analytics. The ideal candidate 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 modeling.

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
  • Define data requirements, gather and mine large scale of structured and unstructured data, and validate data
  • Support standardization, customization and ad hoc data analysis and develop 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
  • Implement processes and systems to drive data reconciliation and monitor data quality
  • Lead the evaluation, implementation and deployment of emerging tools and processes for analytic data engineering
  • Develop and deliver communication and education plans on analytic data engineering capabilities, standards, and processes
  • Solve complex data problems to deliver insights that help achieve business objectives
  • Implement statistical data quality procedures on new data sources

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 data modelling
  • Proven track record of designing and implementing complex data solutions
  • Demonstrated understanding and experience using Data Engineering Programming Languages (i.e., Python)
  • Experience with Distributed Data Technologies (e.g., Pyspark)
  • Familiarity with cloud platform deployment and tools (e.g., Kubernetes)
  • Experience with Relational SQL databases
  • Knowledge of DevOps and continuous integration
  • Experience with AWS cloud services and technologies (i.e., 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
  • Understanding of database architecture and administration
  • High proficiency in code programming languages (e.g., SQL, Python, Pyspark, AWS services)
  • Ability to extract, transform, and load data from multiple external/internal sources using Databricks Lakehouse/Data Lake concepts
  • Utilization of continuous integration and delivery principles to automate deployment of code changes
  • Excellent written and verbal communication skills
  • 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
  • Medical and dental coverage
  • Pension and 401(k) plans
  • Wide range of paid time off options
  • Flexible vacation policy
  • Time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence
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