Home › Jobs › EY › Senior Associate - Data Engineer (AWS Lakehouse, Analytics Engineering Reporting)

Senior Associate - Data Engineer (AWS Lakehouse, Analytics Engineering Reporting)

EY · · Full-time · Senior

Salary Salary not disclosed

About the role

At EY, we develop you with future-focused skills and equip you with world-class experiences. We empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. We work together across our full spectrum of services and skills powered by technology and AI, so that business, people and the planet can thrive together. 

We’re all in, are you? Join EY and shape your future with confidence.

The opportunity

EY DnA is the data and advanced analytics capability within EY Asia-Pacific, with over 500 specialist employees working across multiple industry sectors.

We implement information-driven strategies, data platforms and advanced data analytics solution systems that help grow, optimize and protect client organizations. We go beyond strategy and provide end to end design, build and implementation of real-life data environments and have some of the best architects, project managers, business analysts, data scientists, big data engineers, developers and consultants in the region.

We are seeking an experienced Senior Data Engineer to design, develop, and operate enterprise-scale data platforms supporting analytics, reporting, AI, and operational decision-making. The role focuses on building a secure, governed, and scalable AWS-based Lakehouse platform that enables trusted data products, self-service analytics, enterprise reporting, and AI-ready datasets.

The successful candidate will work across the full data lifecycle, from ingestion and transformation through to governance, reporting, dashboarding, observability, and AI enablement. This role requires strong expertise in AWS data services, modern Lakehouse architectures, Analytics Engineering (dbt), DataOps, and Business Intelligence platforms such as Amazon QuickSight. 

The ideal candidate combines expertise across AWS Data Engineering, Apache Spark, Apache Iceberg, dbt Analytics Engineering, Airflow orchestration, Data Governance (DataZone/Lake Formation), Amazon QuickSight reporting, DataOps automation, and AI-ready data platforms. They should be capable of delivering end-to-end solutions spanning ingestion, transformation, governance, analytics, reporting, dashboard development and AI enablement within secure, mission-critical environments.

Your key responsibilities

1. Data Platform & Lakehouse Engineering

Design, build and maintain enterprise data lakes and Lakehouse architectures using AWS cloud-native technologies.

Implement scalable and secure data storage solutions leveraging Amazon S3 and Apache Iceberg.

Develop and manage Medallion Architecture (Bronze, Silver, Gold) data layers.

Design high-performance data models and optimize storage, partitioning, schema evolution and query performance.

Support batch, near real-time and streaming analytics workloads.

Implement reusable platform services and enterprise data engineering standards.

2. Data Ingestion & Integration

Design and develop metadata-driven data ingestion and ETL/ELT pipelines.

Integrate data from enterprise systems, APIs, databases, operational applications and streaming platforms.

Build scalable ingestion frameworks utilizing:

AWS Glue

AWS Lambda

Amazon EMR

Apache Spark

PySpark

Amazon Kinesis

Amazon MSK (Kafka)

AWS Step Functions

Support both batch and real-time processing requirements.

Develop reusable pipeline frameworks and automation patterns.

3. Analytics Engineering & Data Modelling

Develop and maintain transformation pipelines using dbt (Data Build Tool) .

Build reusable business-ready analytical datasets and semantic models.

Implement automated data lineage, testing, documentation and deployment using dbt.

Create dimensional, star schema and enterprise reporting data models.

Support self-service analytics and data product development initiatives.

Collaborate with business users to translate reporting and analytics requirements into scalable solutions.

4. Reporting & Business Intelligence

Design and develop enterprise reporting solutions and dashboards using Amazon QuickSight .

Build operational, management and executive dashboards to support decision-making.

Develop KPI scorecards, trend analysis reports and performance monitoring dashboards.

Create governed reporting datasets and data marts for business consumption.

Enable self-service reporting while maintaining security and data governance standards.

Optimize reporting performance and user experience for large datasets.

Support ad-hoc analysis, drill-through reporting and interactive visual analytics.

Partner with business stakeholders to define reporting metrics and performance indicators.

5. Data Governance & Metadata Management

Implement enterprise governance capabilities using:

AWS DataZone

AWS Lake Formation

AWS Glue Data Catalog

Support metadata management, business glossary and data stewardship processes.

Implement fine-grained security and access controls.

Manage data classification, lineage and audit requirements.

Support enterprise master and reference data management initiatives.

Ensure compliance with security, privacy and governance standards

6. Data Quality & Observability

Develop automated data quality frameworks and controls.

Implement validation rules, reconciliation processes and anomaly detection.

Monitor pipeline health, data freshness and SLA compliance.

Technologies

AWS Glue Data Quality

Great Expectations

Amazon CloudWatch

Grafana

Prometheus

Key responsibilities include:

Data quality monitoring

Incident response and troubleshooting

Root cause analysis

Platform observability

Performance tuning and optimization

7. DataOps & DevSecOps

Develop and maintain CI/CD pipelines for data engineering workloads.

Implement Infrastructure-as-Code and automated deployment capabilities.

Manage version control, code quality and release management processes.

Apply security-by-design principles across platform development.

Technologies

Terraform

Git

GitLab CI/CD

Docker

Linux

Responsibilities include:

Automated platform provisioning

Environment management

Release automation

Infrastructure compliance

Security remediation and vulnerability management

Skills and attributes for success

AWS Data Platform

Amazon S3

AWS Glue

AWS Glue Data Catalog

AWS Glue Data Quality

Amazon EMR

Amazon Redshift

AWS Lambda

AWS Step Functions

Amazon Kinesis

Amazon MSK

AWS Lake Formation

AWS DataZone

Amazon CloudWatch

AWS IAM

AWS KMS

Amazon QuickSight

Amazon SageMaker

Amazon Bedrock

Open Source & Modern Data Engineering

Data Engineering

Apache Spark

PySpark

Spark SQL

Apache Iceberg

dbt Core

Apache Airflow (AWS MWAA)

Data Quality & Metadata

Great Expectations

OpenLineage (preferred)

OpenMetadata (preferred)

DevOps & Platform Engineering

Terraform

Docker

Git

GitLab

CI/CD

Linux

To qualify for the role, you must have

Min bachelor’s degree in computer science, Mathematics, Engineering, Statistics, or a related field.

3 - 5+ years of Data Engineering experience.

Proven experience delivering AWS-based data platforms and Lakehouse solutions.

Hands-on experience with Spark, dbt, Iceberg and Airflow.

Experience developing enterprise reporting and dashboard solutions using QuickSight.

Experience implementing data governance, metadata management and data quality frameworks.

Exposure to AI, Machine Learning or Generative AI platforms is advantageous.

Prior experience within government, defence, healthcare or highly regulated environments is preferred.

Preferred Certifications

AWS Certified Data Engineer – Associate

AWS Certified Solutions Architect – Associate / Professional

AWS Certified Data Analytics – Specialty

dbt Fundamentals Certification

Databricks Data Engineer Certification (preferred)

Key Competencies

AWS Lakehouse Architecture

Data Engineering & DataOps

Analytics Engineering (dbt)

Enterprise Reporting & Dashboarding

Amazon QuickSight Development

Data Governance & Metadata Management

Data Quality Management

Cloud Security & Compliance

Performance Optimization

Agile Delivery

Stakeholder Management

Technical Leadership

What we look for

Highly motivated individuals with excellent problem-solving skills and the ability to prioritize shifting workloads in a rapidly changing industry.

An effective communicator, you’ll be a confident leader equipped with strong people management skills and a genuine passion to make things happen in a dynamic organization.

What we offer

EY offers a competitive remuneration package commensurate with your work experience where you’ll be rewarded for your individual and team performance. We are committed to being an inclusive employer and are happy to consider flexible working arrangements, where this may be needed, guided by our FWA Policy.

Plus, we offer:

Continuous learning:  You’ll develop the mindset and skills to navigate whatever comes next.

Success as defined by you:  We’ll provide the tools and flexibility, so you can make a meaningful impact, your way.

Transformative leadership:  We’ll give you the insights, coaching and confidence to be the leader the world needs.

Diverse and inclusive culture:  You’ll be embraced for who you are and empowered to use your voice to help others find theirs.

If you can demonstrate that you meet the criteria above, apply today!

Skills

Go SQL Docker Terraform AWS DevOps CI/CD Linux

Applying takes one click with a Tallocate profile, join via your community.