EYData Engineering
About this role
Key Responsibilities
- Responsible for the development, daily operation, and continuous improvement of data infrastructure for a set of analytics products, including ingestion, transformation, quality, and access.
- Co‑develop, test, and maintain Azure Data Factory pipelines to ingest, transform, and orchestrate data from multiple internal and external sources, supporting batch and near‑real‑time processing.
- Create relational and non‑relational databases, including Azure SQL Database and/or Azure Synapse SQL, and contribute to Azure data warehouse and data lake solutions.
- Write and optimize SQL queries and transformations, including stored procedures where appropriate, to support analytics products and downstream insight consumption.
- Assist in automating and scaling data flows using Git‑based workflows and deployment pipelines (e.g., Azure DevOps or GitHub), improving reliability, reuse, and performance.
- Perform daily monitoring of data pipelines and data quality, including validation checks, issue triage, and resolution.
- Maintain data documentation, metadata, and basic lineage tracking.
- Work with analysts and business stakeholders to help define technical requirements for new products.
- Follow established data security, privacy, and governance standards.
- Continue learning modern data engineering tools, platforms, and best practices.
Skills and Attributes for Success
- Demonstrated success in data engineering, analytics engineering, or a closely related technical role.
- Strong proficiency in SQL, including schema design, joins, aggregations, and query optimization.
- Experience working with relational databases (e.g., PostgreSQL, SQL Server, MySQL) and familiarity with non‑relational data stores.
- Experience with Microsoft Azure data services (e.g., Azure SQL, Data Factory, Data Lake), or strong exposure to cloud‑based data platforms.
- Understanding of data warehousing and data lake concepts, including batch and near‑real‑time data processing.
- Experience with ETL/ELT pipelines and data transformation workflows
- Working knowledge of Python or PySpark for data processing and transformation workflows is a plus
- Experience supporting data quality, pipeline monitoring, and issue resolution
- Familiarity with data security, privacy, and governance standards
- Proficiency with modern development workflows, including GitHub‑based collaboration and CI/CD pipelines.
- Experience building and supporting BI and analytics dashboards (e.g., Power BI), including working with DAX and semantic models.
- Effective communication with technical and non‑technical audiences, including translating business needs into technical tasks
- Demonstrated willingness to learn modern data engineering tools and best practices.
What We Look For
- 3 - 5 years of experience in data engineering, analytics, or a related field.
- Interest in building scalable, reliable data infrastructure and products
- A focus on delivering outcomes through continuous improvement
- Curiosity, collaborative mindset and eagerness to learn from teammates
- Comfort working in a fast-paced environment with evolving priorities
What We Offer
- Hands-on experience supporting enterprise data platforms and analytics use cases.
- Structured learning, mentorship, and skill development opportunities.
- Exposure to modern data technologies and best practices.
- A collaborative and inclusive environment focused on growth and impact.
EY | Building a better working world
EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.
Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.
Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.
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EY refers to the global organization, and may refer to one or more, of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity. Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients.
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