Data Foundations Engineer
- Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
- Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
- Design and implement scalable batch and near-real-time data pipelines.
- Develop ETL/ELT workflows optimized for performance and cost.
- Implement dimensional data models and standardize business metrics.
- Instrument APIs and user journeys to capture behavioral and transactional data.
- Ensure data integrity, governance, privacy, and compliance.
- Maintain reliability and availability of mission-critical systems.
- 6+ years of experience in data engineering for analytics or ML systems.
- Strong SQL proficiency.
- 6+yrs experience in Python, Scala, or Java.
- Hands-on experience with Spark, Kafka, and Airflow (or similar).
- Strong understanding of data modeling and lakehouse architectures (e.g., Iceberg).
- Experience with AWS, Azure, or GCP.
- Comfortable participating in rotating on-call.
- Experience with Snowflake, Databricks, Trino, OLAP/NRT systems, Superset or Tableau.
- Familiarity with CI/CD, data observability, infrastructure-as-code.
- Exposure to MLOps and GenAI/RAG pipelines.
- Hands-on experience with LLMs (prompt engineering, fine-tuning, RAG).
- Experience in FinTech, Wallet, or Payments domain.
- Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
- Limited immigration sponsorship may be available
- Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
- Hybrid role - on-site Tue/Wed/Thu
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