Digital-Staff

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GDS Assurance Digital - Staff Software Engineer
Job Title: Data Engineer (Databricks)
Role Level  
Staff    1 - 3 years    

At EY
At EY, we are all in to shape your future with confidence.
We will 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.

About Global Delivery Services
Global Delivery Services refers to EY's worldwide network of service delivery centers. The GDS team plays an important role in EY's strategy by ensuring effective support to EY's growth agenda.
Our journey started in 2002 with approximately 200 people. Today we stand at 80,000+ professionals in ten locations around the world. We operate in Argentina, China, Hungary, India, Philippines, Poland, Sri Lanka, Mexico, Spain and the United Kingdom.
Client service is focused on providing Consulting, Assurance, Tax, Strategy & Transactions, and Knowledge support to our clients around the world. The teams enable account teams worldwide to provide seamless, high-quality, value-added support, helping deliver exceptional client service.
Our innovation specialists serve the GDS Client Service and Enablement Services teams, along with Service Lines, Core Business Services and Sectors. The team brings the desired environment, technologies and skilled teams together for facilitation, rapid prototyping and innovative thinking. The competencies offered include analytics, digital, user experience, mobile technology, infrastructure, Microsoft technologies and open innovation.

Role Overview
We are looking for a motivated and hands-on Staff Data Engineer with working knowledge of Databricks and modern data engineering practices. The candidate will support the development, testing, maintenance, and optimization of data pipelines, help implement data quality checks, assist in data modelling activities, and follow data governance standards. The role will work under the guidance of senior team members and collaborate with business analysts, data architects, data scientists, and analytics teams to deliver reliable data solutions on Azure.

Key Responsibilities
•    Develop, test, and maintain ETL/ELT pipelines using Databricks, PySpark, SQL, and Azure services under guidance from senior team members.
•    Support data ingestion, transformation, and processing for structured and semi-structured data.
•    Implement basic data quality checks, validation rules, and reconciliation controls as per defined standards.
•    Assist in creating and maintaining logical and physical data models aligned with business requirements.
•    Follow enterprise data governance, security, and data management practices while working with data assets.
•    Support performance tuning activities by identifying issues, documenting observations, and applying recommended improvements.
•    Collaborate with business analysts, data scientists, and downstream consumers to understand and fulfil data requirements.
•    Troubleshoot routine data pipeline issues and escalate complex issues with clear documentation.
•    Prepare and maintain technical documentation, runbooks, and operational procedures.
•    Use Databricks Genie Spaces and Genie Code capabilities, where applicable, to improve productivity and support AI-assisted development workflows.

Required Skills
•    Hands-on working knowledge of Databricks.
•    Proficiency in PySpark and SQL.
•    Basic understanding of Azure Data Platform services.
•    Experience in developing or supporting ETL/ELT pipelines.
•    Understanding of data quality management concepts and validation practices.
•    Understanding of RDBMS and basic data modelling concepts such as Star Schema, Snowflake Schema, and Dimensional Modelling.
•    Awareness of data governance, metadata management, and data s