What impact will you make?
Every day, your work will make an impact that matters, while you thrive in a dynamic culture of inclusion, collaboration and high performance. As the undisputed leader in professional services, Deloitte is where you will find unrivaled opportunities to succeed and realize your full potential
Deloitte is where you will find unrivaled opportunities to succeed and realize your full potential.
The Team
Deloitte’s Technology & Transformation practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning.
Learn more about Analytics and Information Management Practice
Work you’ll do
As a Senior Consultant in our Consulting team, you’ll build and nurture positive working relationships with teams and clients with the intention to exceed client expectations. You’ll:
We are seeking experienced AWS Data Engineers to design, implement, and maintain robust data pipelines and analytics solutions using AWS servcies. The ideal candidate will have a strong background in AWS data services, big data technologies, and programming languages.
Key Responsibilities:
1. Design and implement scalable, high-performance data pipelines using AWS services
2. Develop and optimize ETL processes using AWS Glue, EMR, and Lambda
3. Build and maintain data lakes using S3 and Delta Lake
4. Create and manage analytics solutions using Amazon Athena and Redshift
5. Design and implement database solutions using Aurora, RDS, and DynamoDB
6. Develop serverless workflows using AWS Step Functions
7. Write efficient and maintainable code using Python/PySpark, and SQL/PostgrSQL
8. Ensure data quality, security, and compliance with industry standards
9. Collaborate with data scientists and analysts to support their data needs
10. Optimize data architecture for performance and cost-efficiency
11. Troubleshoot and resolve data pipeline and infrastructure issues
Required Qualifications:
1. bachelor’s degree in computer science, Information Technology, or related field
2. Relevant years of experience as a Data Engineer, with at least 60% of experience focusing on AWS
3. Strong proficiency in AWS data services: Glue, EMR, Lambda, Athena, Redshift, S3
4. Experience with data lake technologies, particularly Delta Lake
5. Expertise in database systems: Aurora, RDS, DynamoDB, PostgreSQL
6. Proficiency in Python and PySpark programming
7. Strong SQL skills and experience with PostgreSQL
8. Experience with AWS Step Functions for workflow orchestration
9. Familiarity with data modeling and schema design
10. Knowledge of data security and compliance requirements
11. Excellent problem-solving and analytical skills
12. Strong communication and collaboration abilities
Preferred Qualifications:
1. AWS Certified Data Analytics – Specialty
2. AWS Certified Solutions Architect – Associate or Professional
3. Experience with real-time data processing using Kinesis or Kafka
4. Knowledge of machine learning workflows on AWS (e.g., SageMaker)
5. Familiarity with containerization technologies (Docker, Kubernetes)
6. Experience with CI/CD pipelines and infrastructure-as-code (e.g., CloudFormation, Terraform)
Technical Skills:
– AWS Services: Glue, EMR, Lambda, Athena, Redshift, S3, Aurora, RDS, DynamoDB, Step Functions
– Big Data: Hadoop, Spark, Delta Lake
– Programming: Python, PySpark
– Databases: SQL, PostgreSQL, NoSQL
– Data Warehousing and Analytics
– ETL/ELT processes
– Data Lake architectures
– Version control: Git
– Agile methodologies
