A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe.
You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio; including Software and Red Hat.
Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role you'll be encouraged to challenge the norm investigate ideas outside of your role and come up with creative solutions resulting in ground breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.
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.
What we are looking for:
We are in search of a skilled Consultant Data Engineer to join our expanding team of experts. This role will be pivotal in the design and development of Snowflake Data Cloud solutions encompassing responsibilities such as constructing data ingestion pipelines establishing sound data architecture and implementing stringent data governance and security protocols.
Key Responsibilities
Data Pipeline & Engineering Execution
- Develop and maintain scalable data pipelines and ingestion processes using SQL Python dbt and cloud-native tools.
- Implement ELT/ETL patterns across batch incremental and CDC pipelines.
- Build data models using best practices in Dimensional modeling Data Vault or Lakehouse approaches.
- Support the development of data transformations data quality validations and business logic implementations.
Platform & Cloud Engineering
- Work with cloud platforms (Snowflake Databricks AWS Azure or GCP) to build high-performance cost-efficient data solutions.
- Implement warehouse/lakehouse structures storage standards schema management and governance rules.
- Assist with orchestration using Airflow dbt Cloud or similar tools.
Client Delivery & Consulting Support
- Collaborate with client stakeholders to clarify requirements and translate them into actionable engineering tasks.
- Communicate progress technical decisions and blockers clearly and professionally.
- Participate in client demos stand-ups and architecture discussions representing Hakkoda’s engineering excellence.
- Document technical solutions and contribute to handover materials.
Data Quality Governance & Security
- Implement data validation and monitoring logic to ensure accuracy and reliability.
- Follow security best practices including RBAC data masking encryption and compliance requirements.
- Contribute to documentation standards and engineering templates.
Collaboration & Team Growth
- Work closely with senior engineers and architects to design and refine solutions.
- Participate in code reviews and adopt Hakkoda’s engineering standards.
- Mentor junior engineers as needed and support internal knowledge-sharing sessions.
- Contribute to internal accelerators playbooks and reusable assets.
Continuous Learning & Innovation
- Stay current on cloud data engineering Snowflake Databricks and modern data stack technologies.
- Explore new tools patterns and methodologies that improve engineering efficiency.
- Bring new ideas to the team and participate in innovation initiatives at Hakkoda.
- Experience in Data Engineering or similar roles.
- Strong SQL skills and hands-on experience building data pipelines.
- Proficiency with Python or a similar programming language.
- Experience with at least one cloud data platform (Snowflake Databricks BigQuery Redshift or Synapse).
- Familiarity with data modeling concepts (Dimensional Data Vault Lakehouse).
- Hands-on experience with version control (GitHub Bitbucket) and CICD workflows.
- Experience working in agile collaborative environments.