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Introduction
At IBM, work is more than a job - it's a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you've never thought possible. Are you ready to lead in this new era of technology and solve some of the world's most challenging problems? If so, lets talk.
In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.
Your role and responsibilities
As an AWS Lead Data Engineer, you will play a critical leadership role within the Managed
Services team, focusing on building, optimizing, and supporting a complex Data Lake
architecture. This position requires strong experience in AWS services, team leadership, and
customer collaboration. You’ll design scalable, secure, and efficient solutions while mentoring
your team to deliver outstanding results for our clients.
You will work closely with clients to understand their requirements, provide thought leadership in
AWS architecture, and guide your team in implementing best practices. This role also involves
designing and maintaining data pipelines, monitoring and improving performance, and ensuring
system reliability.
We value open communication, collaboration, and a passion for learning. As a Lead, you will
foster a positive and productive environment while driving technical excellence.
Key Responsibilities
- Design and develop complex Data Lake architectures on AWS, leveraging modern
design patterns and frameworks.
- Build, manage, and optimize ETL/ELT pipelines for large-scale data platforms using tools like AWS Glue, EMR, and AWS Batch Service.
- Lead the implementation of AWS Lambda functions for automation and event-driven processes.
- Implement and optimize solutions using IoT TimeStream Database for time-series data and DynamoDB for NoSQL workloads.
- Guide the team in leveraging SageMaker for machine learning model development and deployment.
- Develop robust IAM policies to ensure security, compliance, and proper access controls across all environments.
- Provide thought leadership in using AWS services, tools, and best practices to improve system performance and reliability.
- Mentor and coach team members, fostering professional growth and knowledge sharing.
- Collaborate with internal and client teams to identify problems, prevent incidents, and deliver solutions that meet business goals.
- Monitor the production environment holistically, ensuring system health, reliability, and performance.
- Manage and prioritize multiple client engagements, including incident resolution,
enhancements, and infrastructure optimization.
As of April 2025, Hakkoda has been acquired by IBM and will be integrated in the IBM organization. Your recruitment process will be managed by IBM. IBM will be the hiring entity.
Required education
Bachelor's Degree
Required technical and professional expertise
Experience
- 4+ years of experience in technical roles, including 1+ year in a leadership or
management role.
- Proven experience designing, building, and maintaining complex Data Lakes on AWS for large-scale distributed systems.
- Strong understanding of AWS architecture and services, including but not limited to:
○ AWS Glue, EMR, AWS Batch, Lambda, SageMaker, IoT TimeStream,
DynamoDB.
- Demonstrated experience in leading and mentoring technical teams.
Technical Skills
- Advanced expertise in SQL, including performance tuning and query optimization.
- Proficiency in Python for automation, scripting, and data processing.
- Strong experience with ETL/ELT pipelines and data warehouse solutions (e.g., Teradata, Netezza, Oracle Exadata, Snowflake, SQL Server).
- Familiarity with data visualization tools like Power BI, Tableau, or Looker.
- Working knowledge of business intelligence/data analytics.
- Cloud expertise with a focus on AWS; experience with Snowflake or other cloud
platforms (Azure, GCP) is a plus.
Leadership and Soft Skills
- Experience hiring, developing, and managing technical teams, fostering a collaborative and innovative culture.
- Strong organizational and project management skills, including working in Agile
environments.
- A proactive, solutions-oriented mindset, with the ability to identify and address
performance bottlenecks.
- Excellent communication skills, with the ability to engage technical and non-technical stakeholders.
- Advanced English proficiency (written and spoken).
Education
- Bachelor’s degree in Data Analytics, Computer Science, Management Information
Systems, Mathematics, or a related technical field.
Preferred technical and professional experience
- Certification in AWS (e.g., AWS Certified Solutions Architect, AWS Certified Data
Analytics – Specialty).
- Experience with Snowflake and its integration with AWS platforms.
- Familiarity with data governance practices and frameworks.
- Knowledge of streaming technologies such as Apache Kafka or AWS Kinesis.
- Certifications such as Data Vault 2.0 Practitioner or other data warehouse design
standards.