Senior AI Data Engineer

Job not on LinkedIn

🕒 September 25

🌐 Mexico, Argentina – Remote

🇲🇽 Mexico – Remote 🇦🇷 Argentina – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 18%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Strategic Systems International

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1991

🏥 Healthcare

💼 Consulting

📦 Logistics

Healthcare • Consulting • Logistics

Strategic Systems International (SSI) is a technology services company focused on providing innovative software solutions. With three decades of experience, SSI empowers businesses through advanced data services, artificial intelligence, and cloud computing. Their expertise spans various industries, including financial services, healthcare, and industrial supply chain. SSI's services include AI/ML, digital transformation, and SaaS applications, helping clients optimize their operations and make informed decisions. SSI is dedicated to merging physical and digital worlds, enhancing efficiency and productivity for a broad range of clients from startups to Fortune 500 companies.

📋 Description

• Design and operate the data foundation supporting AI systems • Own movement, modeling, and quality of data from source systems through the warehouse into retrieval and feature layers • Build and maintain data pipelines powering LLM pipelines, agentic workflows, and analytical products • Model warehouse schemas and make decisions about grain, relationships, and denormalization • Write production Python and maintain pipelines as versioned, tested, observable software • Partner with the AI/ML Data Scientist, who owns model behavior and retrieval strategy • Own the pipeline, schema, and data guarantees while collaborating on the algorithm, prompt, and evaluation boundary

🎯 Requirements

• 5-10+ years in software engineering or data engineering, with substantial time in production data platform work • Demonstrable command of Kimball dimensional modeling, including choosing grain, resolving many-to-many relationships, and denormalization decisions • Working knowledge of Data Vault, One Big Table, Inman, and tradeoffs against Kimball • Expert-level SQL: window functions, CTEs, query plan reading, and performance tuning on a columnar warehouse • Expert-level, production-grade Python: typing, packaging, dependency management, and testing • Experience applying SOLID and domain-driven design in real systems • Production experience with Airflow, Prefect, Dagster, or equivalent • Expert-level experience with AWS, Azure, or GCP, including storage, compute, IAM, networking, and cost management • Experience with containerization, Kubernetes (EKS/AKS/GKE), and CI/CD • Experience with lakehouse table formats such as Iceberg, Delta Lake, or Hudi, including compaction, snapshot expiry, schema evolution, and partition evolution • Preferred: experience building data layers beneath production RAG systems, including hybrid search infrastructure and index freshness guarantees • Preferred: experience with Kafka, Kinesis, Flink, or Spark Structured Streaming • Preferred: dbt or equivalent transformation and testing framework • Preferred: data quality tooling such as Great Expectations or Soda, and catalog/lineage platforms • Preferred: familiarity with MLflow, Weights & Biases, and feature stores • Preferred: working knowledge of a second language: TypeScript, Java, Go, Scala, or Rust • Preferred: experience with AI security, governance, and compliance frameworks • Preferred: open-source contributions to data or AI infrastructure projects

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