Senior Data Engineer / AI Data Platform Engineer (Spark / ETL / Cloud)

Location: Santo Domingo Dominican Republic (On-site Hybrid Remote flexibility)
Employment Type: Full-Time
Industry: AI / Software Engineering / Data Platforms

About the Role

We are looking for a Senior Data Engineer / AI Data Platform Engineer to design and build high-performance scalable data pipelines that power AI/ML systems and data-driven applications.

This role goes beyond traditional ETL it focuses on distributed computing large-scale data processing and data infrastructure for AI workloads using technologies like Apache Spark Python and cloud-native architectures.

You will play a key role in enabling machine learning pipelines real-time data processing and high-volume data systems.

Key Responsibilities

• Design and build scalable data pipelines for AI/ML workloads
• Develop distributed data processing systems using Apache Spark (batch & streaming)
• Optimize large-scale data transformations using Python and SQL
• Architect and maintain data platforms on AWS Azure or Google Cloud
• Implement parallel processing partitioning strategies and performance tuning
• Enable data ingestion pipelines for structured and unstructured data (logs events APIs)
• Collaborate with ML Engineers and Software Engineers to support AI models
• Ensure data reliability observability and system scalability

Technical Requirements (MUST HAVE)

• Strong experience with Apache Spark (core performance optimization)
• Advanced SQL (analytical optimization level)
• Strong programming in Python (data performance oriented)
• Proven experience building ETL / ELT pipelines at scale
• Experience with cloud-native architectures (AWS Azure or GCP)
• Deep understanding of distributed systems and data processing at scale
• Experience handling large datasets (10M1B records)

Nice to Have (Highly Valued in AI Market)

• Experience supporting ML pipelines (feature engineering data prep)
• Familiarity with Spark Streaming / Kafka / real-time pipelines
• Experience with Databricks / Snowflake / BigQuery
• Knowledge of data lakehouse architectures
• Experience with containerization (Docker Kubernetes)
• Exposure to MLOps workflows

What We Offer

• Competitive salary aligned with AI/Engineering market (USD-based)
• Flexible work model (Hybrid Remote)
• Opportunity to work on AI-driven systems and scalable platforms
• High-impact engineering environment (not BI / not reporting-focused)

Application Requirements (MANDATORY)

To be considered candidates MUST submit:

1. Updated Resume (CV)
2. Updated LinkedIn profile link
3. A short written response including:

Why should you be considered for this role

Please include:

• Your experience with Apache Spark and distributed data systems
• A description of the most complex data pipeline or system you have built
• Your experience working with large-scale data or AI-related systems
• Why you are a strong fit for this position

Professional Summary (35 lines)

Provide a concise summary of your experience as a Data Engineer / AI Data Engineer.

Li SEO Keywords (AI / Engineering Focus)

(keep small when posting)

Senior Data Engineer AI Data Engineer Data Platform Engineer Apache Spark Distributed Systems Big Data Python SQL AWS Azure GCP Machine Learning Data Pipelines Data Infrastructure Spark Streaming Kafka Databricks Data Lakehouse MLOps Cloud Engineering Scalable Systems