Senior Global Data ML Engineer – Multilingual Speech AI

Cartesia; San Francisco (CA); On-site; USD 103,000 - 171,000; Full time

Job summary

Deloitte is seeking a Global Data ML Engineer for Multilingual Speech AI in the San Francisco area to design and manage scalable data pipelines on AWS and Snowflake. You will transform source data into analytics-ready datasets and build robust ETL/ELT processes across teams.

The role requires 7+ years of experience in data engineering, Python/SQL, and experience with Lakehouse architectures, with some travel to client sites. Hybrid/onsite collaboration is common in this engagement.

Qualifications

• 7+ years of experience delivering production-grade data pipelines and curated datasets.
• 7+ years of hands-on experience with SQL and Python, including Snowflake and/or PySpark for scalable data processing and ELT.
• 7+ years of experience designing, building, and operating batch and near-real-time data pipelines on cloud platforms (AWS preferred; Azure/GCP acceptable).
• Experience with data integration frameworks and orchestration tools.
• Proficiency in designing and implementing Lakehouse/warehouse architectures and ELT patterns.
• Knowledge of DevOps principles: CI/CD pipelines, version control, Infrastructure-as-Code.
• Ability to optimise data storage, partitioning, file formats (Delta, Parquet), and performance.
• Understanding of data quality, data governance, and metadata management.

Responsibilities

• Architect, build, and operate scalable batch and near-real-time data pipelines on AWS.
• Design robust ingestion patterns from source systems into S3 and into Snowflake.
• Develop transformation layers and curated datasets in Snowflake, including dimensional/data product modeling for analytics and downstream applications.
• Implement orchestration and workflow automation on AWS with retries, backfills, and idempotency.
• Build reusable Python components for ingestion, validation, and transformations; enforce standards via code reviews and testing.
• Optimize Snowflake performance and cost warehouse sizing, concurrency patterns, query tuning, clustering/micro-partition considerations, and workload isolation.
• Partner with stakeholders to translate requirements into well-defined datasets and data contracts.
• Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various teams, escalating as needed.
• Independently and collaboratively lead client engagement workstreams focused on improvement, optimisation, and transformation of processes.

Skills

SQL

Python

Snowflake

PySpark

AWS

ETL

Data Pipelines

DevOps

CI/CD

Data Governance

Education

Bachelor's degree

Tools

Airflow

Job description

Deloitte is seeking a Global Data ML Engineer for Multilingual Speech AI in the San Francisco area to design and manage scalable data pipelines on AWS and Snowflake. You will transform source data into analytics-ready datasets and build robust ETL/ELT processes across teams.

The role requires 7+ years of experience in data engineering, Python/SQL, and experience with Lakehouse architectures, with some travel to client sites. Hybrid/onsite collaboration is common in this engagement.